diff --git a/examples/parallel/CMakeLists.txt b/examples/parallel/CMakeLists.txt
new file mode 100644
index 0000000..153c422
--- /dev/null
+++ b/examples/parallel/CMakeLists.txt
@@ -0,0 +1,3 @@
+set(TARGET parallel)
+add_executable(${TARGET} parallel.cpp)
+target_link_libraries(${TARGET} PRIVATE whisper ${CMAKE_THREAD_LIBS_INIT})
diff --git a/examples/parallel/README.md b/examples/parallel/README.md
new file mode 100644
index 0000000..919537b
--- /dev/null
+++ b/examples/parallel/README.md
@@ -0,0 +1,3 @@
+# parallel
+
+TODO
diff --git a/examples/parallel/parallel.cpp b/examples/parallel/parallel.cpp
new file mode 100644
index 0000000..91e4a37
--- /dev/null
+++ b/examples/parallel/parallel.cpp
@@ -0,0 +1,422 @@
+#include "whisper.h"
+
+// third-party utilities
+// use your favorite implementations
+#define DR_WAV_IMPLEMENTATION
+#include "dr_wav.h"
+
+#include <cmath>
+#include <fstream>
+#include <cstdio>
+#include <string>
+#include <thread>
+#include <vector>
+
+// Terminal color map. 10 colors grouped in ranges [0.0, 0.1, ..., 0.9]
+// Lowest is red, middle is yellow, highest is green.
+const std::vector<std::string> k_colors = {
+    "\033[38;5;196m", "\033[38;5;202m", "\033[38;5;208m", "\033[38;5;214m", "\033[38;5;220m",
+    "\033[38;5;226m", "\033[38;5;190m", "\033[38;5;154m", "\033[38;5;118m", "\033[38;5;82m",
+};
+
+//  500 -> 00:05.000
+// 6000 -> 01:00.000
+std::string to_timestamp(int64_t t, bool comma = false) {
+    int64_t msec = t * 10;
+    int64_t hr = msec / (1000 * 60 * 60);
+    msec = msec - hr * (1000 * 60 * 60);
+    int64_t min = msec / (1000 * 60);
+    msec = msec - min * (1000 * 60);
+    int64_t sec = msec / 1000;
+    msec = msec - sec * 1000;
+
+    char buf[32];
+    snprintf(buf, sizeof(buf), "%02d:%02d:%02d%s%03d", (int) hr, (int) min, (int) sec, comma ? "," : ".", (int) msec);
+
+    return std::string(buf);
+}
+
+// command-line parameters
+struct whisper_params {
+    int32_t seed        = -1; // RNG seed, not used currently
+    int32_t n_threads   = std::min(4, (int32_t) std::thread::hardware_concurrency());
+    int32_t offset_t_ms = 0;
+    int32_t offset_n    = 0;
+
+    bool verbose              = false;
+    bool translate            = false;
+    bool output_txt           = false;
+    bool output_vtt           = false;
+    bool output_srt           = false;
+    bool print_special_tokens = false;
+    bool print_colors         = false;
+    bool no_timestamps        = false;
+
+    std::string language  = "en";
+    std::string model     = "models/ggml-base.en.bin";
+
+    std::vector<std::string> fname_inp = {};
+};
+
+void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
+
+bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
+    for (int i = 1; i < argc; i++) {
+        std::string arg = argv[i];
+
+        if (arg[0] != '-') {
+            params.fname_inp.push_back(arg);
+            continue;
+        }
+
+        if (arg == "-s" || arg == "--seed") {
+            params.seed = std::stoi(argv[++i]);
+        } else if (arg == "-t" || arg == "--threads") {
+            params.n_threads = std::stoi(argv[++i]);
+        } else if (arg == "-ot" || arg == "--offset-t") {
+            params.offset_t_ms = std::stoi(argv[++i]);
+        } else if (arg == "-on" || arg == "--offset-n") {
+            params.offset_n = std::stoi(argv[++i]);
+        } else if (arg == "-v" || arg == "--verbose") {
+            params.verbose = true;
+        } else if (arg == "--translate") {
+            params.translate = true;
+        } else if (arg == "-l" || arg == "--language") {
+            params.language = argv[++i];
+            if (whisper_lang_id(params.language.c_str()) == -1) {
+                fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
+                whisper_print_usage(argc, argv, params);
+                exit(0);
+            }
+        } else if (arg == "-otxt" || arg == "--output-txt") {
+            params.output_txt = true;
+        } else if (arg == "-ovtt" || arg == "--output-vtt") {
+            params.output_vtt = true;
+        } else if (arg == "-osrt" || arg == "--output-srt") {
+            params.output_srt = true;
+        } else if (arg == "-ps" || arg == "--print_special") {
+            params.print_special_tokens = true;
+        } else if (arg == "-pc" || arg == "--print_colors") {
+            params.print_colors = true;
+        } else if (arg == "-nt" || arg == "--no_timestamps") {
+            params.no_timestamps = true;
+        } else if (arg == "-m" || arg == "--model") {
+            params.model = argv[++i];
+        } else if (arg == "-f" || arg == "--file") {
+            params.fname_inp.push_back(argv[++i]);
+        } else if (arg == "-h" || arg == "--help") {
+            whisper_print_usage(argc, argv, params);
+            exit(0);
+        } else {
+            fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
+            whisper_print_usage(argc, argv, params);
+            exit(0);
+        }
+    }
+
+    return true;
+}
+
+void whisper_print_usage(int argc, char ** argv, const whisper_params & params) {
+    fprintf(stderr, "\n");
+    fprintf(stderr, "usage: %s [options] file0.wav file1.wav ...\n", argv[0]);
+    fprintf(stderr, "\n");
+    fprintf(stderr, "options:\n");
+    fprintf(stderr, "  -h,       --help           show this help message and exit\n");
+    fprintf(stderr, "  -s SEED,  --seed SEED      RNG seed (default: -1)\n");
+    fprintf(stderr, "  -t N,     --threads N      number of threads to use during computation (default: %d)\n", params.n_threads);
+    fprintf(stderr, "  -ot N,    --offset-t N     time offset in milliseconds (default: %d)\n", params.offset_t_ms);
+    fprintf(stderr, "  -on N,    --offset-n N     segment index offset (default: %d)\n", params.offset_n);
+    fprintf(stderr, "  -v,       --verbose        verbose output\n");
+    fprintf(stderr, "            --translate      translate from source language to english\n");
+    fprintf(stderr, "  -otxt,    --output-txt     output result in a text file\n");
+    fprintf(stderr, "  -ovtt,    --output-vtt     output result in a vtt file\n");
+    fprintf(stderr, "  -osrt,    --output-srt     output result in a srt file\n");
+    fprintf(stderr, "  -ps,      --print_special  print special tokens\n");
+    fprintf(stderr, "  -pc,      --print_colors   print colors\n");
+    fprintf(stderr, "  -nt,      --no_timestamps  do not print timestamps\n");
+    fprintf(stderr, "  -l LANG,  --language LANG  spoken language (default: %s)\n", params.language.c_str());
+    fprintf(stderr, "  -m FNAME, --model FNAME    model path (default: %s)\n", params.model.c_str());
+    fprintf(stderr, "  -f FNAME, --file FNAME     input WAV file path\n");
+    fprintf(stderr, "\n");
+}
+
+void whisper_print_segment_callback(struct whisper_context * ctx, void * user_data) {
+    const whisper_params & params = *(whisper_params *) user_data;
+
+    const int n_segments = whisper_full_n_segments(ctx);
+
+    // print the last segment
+    const int i = n_segments - 1;
+    if (i == 0) {
+        printf("\n");
+    }
+
+    if (params.no_timestamps) {
+        if (params.print_colors) {
+            for (int j = 0; j < whisper_full_n_tokens(ctx, i); ++j) {
+                if (params.print_special_tokens == false) {
+                    const whisper_token id = whisper_full_get_token_id(ctx, i, j);
+                    if (id >= whisper_token_eot(ctx)) {
+                        continue;
+                    }
+                }
+
+                const char * text = whisper_full_get_token_text(ctx, i, j);
+                const float  p    = whisper_full_get_token_p   (ctx, i, j);
+
+                const int col = std::max(0, std::min((int) k_colors.size(), (int) (std::pow(p, 3)*float(k_colors.size()))));
+
+                printf("%s%s%s", k_colors[col].c_str(), text, "\033[0m");
+            }
+        } else {
+            const char * text = whisper_full_get_segment_text(ctx, i);
+            printf("%s", text);
+        }
+        fflush(stdout);
+    } else {
+        const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
+        const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
+
+        if (params.print_colors) {
+            printf("[%s --> %s]  ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str());
+            for (int j = 0; j < whisper_full_n_tokens(ctx, i); ++j) {
+                if (params.print_special_tokens == false) {
+                    const whisper_token id = whisper_full_get_token_id(ctx, i, j);
+                    if (id >= whisper_token_eot(ctx)) {
+                        continue;
+                    }
+                }
+
+                const char * text = whisper_full_get_token_text(ctx, i, j);
+                const float  p    = whisper_full_get_token_p   (ctx, i, j);
+
+                const int col = std::max(0, std::min((int) k_colors.size(), (int) (std::pow(p, 3)*float(k_colors.size()))));
+
+                printf("%s%s%s", k_colors[col].c_str(), text, "\033[0m");
+            }
+            printf("\n");
+        } else {
+            const char * text = whisper_full_get_segment_text(ctx, i);
+
+            printf("[%s --> %s]  %s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), text);
+        }
+    }
+}
+
+bool output_txt(struct whisper_context * ctx, const char * fname) {
+    std::ofstream fout(fname);
+    if (!fout.is_open()) {
+        fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
+        return false;
+    }
+
+    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
+
+    const int n_segments = whisper_full_n_segments(ctx);
+    for (int i = 0; i < n_segments; ++i) {
+        const char * text = whisper_full_get_segment_text(ctx, i);
+        fout << text;
+    }
+
+    return true;
+}
+
+bool output_vtt(struct whisper_context * ctx, const char * fname) {
+    std::ofstream fout(fname);
+    if (!fout.is_open()) {
+        fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
+        return 9;
+    }
+
+    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
+
+    fout << "WEBVTT\n\n";
+
+    const int n_segments = whisper_full_n_segments(ctx);
+    for (int i = 0; i < n_segments; ++i) {
+        const char * text = whisper_full_get_segment_text(ctx, i);
+        const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
+        const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
+
+        fout << to_timestamp(t0) << " --> " << to_timestamp(t1) << "\n";
+        fout << text << "\n\n";
+    }
+
+    return true;
+}
+
+bool output_srt(struct whisper_context * ctx, const char * fname, const whisper_params & params) {
+    std::ofstream fout(fname);
+    if (!fout.is_open()) {
+        fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
+        return false;
+    }
+
+    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
+
+    const int n_segments = whisper_full_n_segments(ctx);
+    for (int i = 0; i < n_segments; ++i) {
+        const char * text = whisper_full_get_segment_text(ctx, i);
+        const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
+        const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
+
+        fout << i + 1 + params.offset_n << "\n";
+        fout << to_timestamp(t0, true) << " --> " << to_timestamp(t1, true) << "\n";
+        fout << text << "\n\n";
+    }
+
+    return true;
+}
+
+int main(int argc, char ** argv) {
+    whisper_params params;
+
+    if (whisper_params_parse(argc, argv, params) == false) {
+        return 1;
+    }
+
+    if (params.seed < 0) {
+        params.seed = time(NULL);
+    }
+
+    if (params.fname_inp.empty()) {
+        fprintf(stderr, "error: no input files specified\n");
+        whisper_print_usage(argc, argv, params);
+        return 2;
+    }
+
+    // whisper init
+
+    struct whisper_context * ctx = whisper_init(params.model.c_str());
+
+    if (ctx == nullptr) {
+        fprintf(stderr, "error: failed to initialize whisper context\n");
+        return 3;
+    }
+
+    for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
+        const auto fname_inp = params.fname_inp[f];
+
+        // WAV input
+        std::vector<float> pcmf32;
+        {
+            drwav wav;
+            if (!drwav_init_file(&wav, fname_inp.c_str(), NULL)) {
+                fprintf(stderr, "%s: failed to open WAV file '%s' - check your input\n", argv[0], fname_inp.c_str());
+                whisper_print_usage(argc, argv, {});
+                return 4;
+            }
+
+            if (wav.channels != 1 && wav.channels != 2) {
+                fprintf(stderr, "%s: WAV file '%s' must be mono or stereo\n", argv[0], fname_inp.c_str());
+                return 5;
+            }
+
+            if (wav.sampleRate != WHISPER_SAMPLE_RATE) {
+                fprintf(stderr, "%s: WAV file '%s' must be 16 kHz\n", argv[0], fname_inp.c_str());
+                return 6;
+            }
+
+            if (wav.bitsPerSample != 16) {
+                fprintf(stderr, "%s: WAV file '%s' must be 16-bit\n", argv[0], fname_inp.c_str());
+                return 7;
+            }
+
+            int n = wav.totalPCMFrameCount;
+
+            std::vector<int16_t> pcm16;
+            pcm16.resize(n*wav.channels);
+            drwav_read_pcm_frames_s16(&wav, n, pcm16.data());
+            drwav_uninit(&wav);
+
+            // convert to mono, float
+            pcmf32.resize(n);
+            if (wav.channels == 1) {
+                for (int i = 0; i < n; i++) {
+                    pcmf32[i] = float(pcm16[i])/32768.0f;
+                }
+            } else {
+                for (int i = 0; i < n; i++) {
+                    pcmf32[i] = float(pcm16[2*i] + pcm16[2*i + 1])/65536.0f;
+                }
+            }
+        }
+
+        // print system information
+        {
+            fprintf(stderr, "\n");
+            fprintf(stderr, "system_info: n_threads = %d / %d | %s\n", params.n_threads, std::thread::hardware_concurrency(), whisper_print_system_info());
+        }
+
+        // print some info about the processing
+        {
+            fprintf(stderr, "\n");
+            if (!whisper_is_multilingual(ctx)) {
+                if (params.language != "en" || params.translate) {
+                    params.language = "en";
+                    params.translate = false;
+                    fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
+                }
+            }
+            fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, lang = %s, task = %s, timestamps = %d ...\n",
+                    __func__, fname_inp.c_str(), int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE, params.n_threads,
+                    params.language.c_str(),
+                    params.translate ? "translate" : "transcribe",
+                    params.no_timestamps ? 0 : 1);
+
+            fprintf(stderr, "\n");
+        }
+
+
+        // run the inference
+        {
+            whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
+
+            wparams.print_realtime       = false;
+            wparams.print_progress       = false;
+            wparams.print_timestamps     = !params.no_timestamps;
+            wparams.print_special_tokens = params.print_special_tokens;
+            wparams.translate            = params.translate;
+            wparams.language             = params.language.c_str();
+            wparams.n_threads            = params.n_threads;
+            wparams.offset_ms            = params.offset_t_ms;
+
+            // this callback is called on each new segment
+            if (!wparams.print_realtime) {
+                wparams.new_segment_callback           = whisper_print_segment_callback;
+                wparams.new_segment_callback_user_data = &params;
+            }
+
+            if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
+                fprintf(stderr, "%s: failed to process audio\n", argv[0]);
+                return 8;
+            }
+
+            printf("\n");
+
+            // output to text file
+            if (params.output_txt) {
+                const auto fname_txt = fname_inp + ".txt";
+                output_txt(ctx, fname_txt.c_str());
+            }
+
+            // output to VTT file
+            if (params.output_vtt) {
+                const auto fname_vtt = fname_inp + ".vtt";
+                output_vtt(ctx, fname_vtt.c_str());
+            }
+
+            // output to SRT file
+            if (params.output_srt) {
+                const auto fname_srt = fname_inp + ".srt";
+                output_srt(ctx, fname_srt.c_str(), params);
+            }
+        }
+    }
+
+    whisper_print_timings(ctx);
+    whisper_free(ctx);
+
+    return 0;
+}
diff --git a/whisper.cpp b/whisper.cpp
index f42976d..ee8d994 100644
--- a/whisper.cpp
+++ b/whisper.cpp
@@ -413,7 +413,6 @@ struct whisper_context {
     std::vector<float> probs;
     std::vector<float> logits;
 
-    std::vector<whisper_token_data> tokens_cur;
     std::vector<whisper_segment> result_all;
 
     std::vector<whisper_token> prompt_past;
@@ -430,7 +429,7 @@ struct whisper_context {
 //
 // see the convert-pt-to-ggml.py script for details
 //
-bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
+bool whisper_model_load(const std::string & fname, const int n_processors, whisper_context & wctx) {
     fprintf(stderr, "%s: loading model from '%s'\n", __func__, fname.c_str());
 
     auto & model = wctx.model;
@@ -700,11 +699,11 @@ bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
             ctx_size += n_text_layer*(             n_text_state*ggml_type_size(GGML_TYPE_F32)); // cross_attn_ln_1_b
         }
 
-        ctx_size += n_text_layer*n_text_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_k
-        ctx_size += n_text_layer*n_text_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_v
+        ctx_size += n_processors*n_text_layer*n_text_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_k
+        ctx_size += n_processors*n_text_layer*n_text_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_v
 
-        ctx_size += n_text_layer*n_audio_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_cross_k
-        ctx_size += n_text_layer*n_audio_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_cross_v
+        ctx_size += n_processors*n_text_layer*n_audio_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_cross_k
+        ctx_size += n_processors*n_text_layer*n_audio_ctx*n_text_state*ggml_type_size(GGML_TYPE_F16); // memory_cross_v
 
         ctx_size += (15 + 15*n_audio_layer + 24*n_text_layer)*256; // object overhead
 
@@ -934,7 +933,7 @@ bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
         // key/value memory for the self-attention layer
         {
             const int n_mem      = n_text_layer*n_text_ctx;
-            const int n_elements = n_text_state*n_mem;
+            const int n_elements = n_text_state*n_mem*n_processors;
 
             model.memory_k = ggml_new_tensor_1d(ctx, GGML_TYPE_F16, n_elements);
             model.memory_v = ggml_new_tensor_1d(ctx, GGML_TYPE_F16, n_elements);
@@ -945,7 +944,7 @@ bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
             const int n_audio_ctx   = hparams.n_audio_ctx;
 
             const int n_mem      = n_text_layer*n_audio_ctx;
-            const int n_elements = n_text_state*n_mem;
+            const int n_elements = n_text_state*n_mem*n_processors;
 
             model.memory_cross_k = ggml_new_tensor_1d(ctx, GGML_TYPE_F16, n_elements);
             model.memory_cross_v = ggml_new_tensor_1d(ctx, GGML_TYPE_F16, n_elements);
@@ -955,7 +954,7 @@ bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
             ggml_nbytes(model.memory_k)       + ggml_nbytes(model.memory_v) +
             ggml_nbytes(model.memory_cross_k) + ggml_nbytes(model.memory_cross_v);
 
-        fprintf(stderr, "%s: memory size = %8.2f MB \n", __func__, memory_size/1024.0/1024.0);
+        fprintf(stderr, "%s: memory size = %8.2f MB (%d processors)\n", __func__, memory_size/1024.0/1024.0, n_processors);
     }
 
     // load weights
@@ -1046,7 +1045,8 @@ bool whisper_model_load(const std::string & fname, whisper_context & wctx) {
 bool whisper_encode(
               whisper_context & wctx,
         const int n_threads,
-        const int mel_offset) {
+        const int mel_offset,
+        const int processor_id) {
     const auto & model   = wctx.model;
     const auto & mel_inp = wctx.mel;
     const auto & hparams = model.hparams;
@@ -1400,8 +1400,11 @@ bool whisper_encode(
                         Vcross),
                     Vcross);
 
-            struct ggml_tensor * k = ggml_view_1d(ctx0, model.memory_cross_k, n_state*n_ctx, (ggml_element_size(model.memory_cross_k)*n_state)*(il*n_ctx));
-            struct ggml_tensor * v = ggml_view_1d(ctx0, model.memory_cross_v, n_state*n_ctx, (ggml_element_size(model.memory_cross_v)*n_state)*(il*n_ctx));
+            const size_t offset_k = processor_id*(ggml_element_size(model.memory_cross_k)*n_state)*(model.hparams.n_text_layer*n_ctx);
+            const size_t offset_v = processor_id*(ggml_element_size(model.memory_cross_v)*n_state)*(model.hparams.n_text_layer*n_ctx);
+
+            struct ggml_tensor * k = ggml_view_1d(ctx0, model.memory_cross_k, n_state*n_ctx, offset_k + (ggml_element_size(model.memory_cross_k)*n_state)*(il*n_ctx));
+            struct ggml_tensor * v = ggml_view_1d(ctx0, model.memory_cross_v, n_state*n_ctx, offset_v + (ggml_element_size(model.memory_cross_v)*n_state)*(il*n_ctx));
 
             ggml_build_forward_expand(&gf, ggml_cpy(ctx0, Kcross, k));
             ggml_build_forward_expand(&gf, ggml_cpy(ctx0, Vcross, v));
@@ -1434,7 +1437,8 @@ bool whisper_decode(
         const int n_threads,
         const whisper_token * tokens,
         const int n_tokens,
-        const int n_past) {
+        const int n_past,
+        const int processor_id) {
     const auto & model   = wctx.model;
     const auto & hparams = model.hparams;
 
@@ -1529,10 +1533,13 @@ bool whisper_decode(
                         Vcur),
                     Vcur);
 
+            const size_t offset_k = processor_id*(ggml_element_size(model.memory_k)*n_state)*(n_layer*n_ctx);
+            const size_t offset_v = processor_id*(ggml_element_size(model.memory_v)*n_state)*(n_layer*n_ctx);
+
             // store key and value to memory
             {
-                struct ggml_tensor * k = ggml_view_1d(ctxL, model.memory_k, N*n_state, (ggml_element_size(model.memory_k)*n_state)*(il*n_ctx + n_past));
-                struct ggml_tensor * v = ggml_view_1d(ctxL, model.memory_v, N*n_state, (ggml_element_size(model.memory_v)*n_state)*(il*n_ctx + n_past));
+                struct ggml_tensor * k = ggml_view_1d(ctxL, model.memory_k, N*n_state, offset_k + (ggml_element_size(model.memory_k)*n_state)*(il*n_ctx + n_past));
+                struct ggml_tensor * v = ggml_view_1d(ctxL, model.memory_v, N*n_state, offset_v + (ggml_element_size(model.memory_v)*n_state)*(il*n_ctx + n_past));
 
                 ggml_build_forward_expand(&gf, ggml_cpy(ctxL, Kcur, k));
                 ggml_build_forward_expand(&gf, ggml_cpy(ctxL, Vcur, v));
@@ -1550,7 +1557,7 @@ bool whisper_decode(
             struct ggml_tensor * K =
                 ggml_permute(ctxL,
                         ggml_reshape_3d(ctxL,
-                            ggml_view_1d(ctxL, model.memory_k, (n_past + N)*n_state, il*n_ctx*ggml_element_size(model.memory_k)*n_state),
+                            ggml_view_1d(ctxL, model.memory_k, (n_past + N)*n_state, offset_k + il*n_ctx*ggml_element_size(model.memory_k)*n_state),
                             n_state/n_head, n_head, n_past + N),
                         0, 2, 1, 3);
 
@@ -1570,7 +1577,7 @@ bool whisper_decode(
             struct ggml_tensor * V_trans =
                 ggml_permute(ctxL,
                         ggml_reshape_3d(ctxL,
-                            ggml_view_1d(ctxL, model.memory_v, (n_past + N)*n_state, il*n_ctx*ggml_element_size(model.memory_v)*n_state),
+                            ggml_view_1d(ctxL, model.memory_v, (n_past + N)*n_state, offset_v + il*n_ctx*ggml_element_size(model.memory_v)*n_state),
                             n_state/n_head, n_head, n_past + N),
                         1, 2, 0, 3);
 
@@ -1622,15 +1629,18 @@ bool whisper_decode(
 
             Qcur = ggml_scale(ctxL, Qcur, ggml_new_f32(ctxL, pow(float(n_state)/n_head, -0.25)));
 
+            const size_t offset_k = processor_id*(ggml_element_size(model.memory_cross_k)*n_state)*(n_layer*M);
+            const size_t offset_v = processor_id*(ggml_element_size(model.memory_cross_v)*n_state)*(n_layer*M);
+
             // Kcross is already scaled
             struct ggml_tensor * Kcross =
                 ggml_reshape_3d(ctxL,
-                        ggml_view_1d(ctxL, model.memory_cross_k, M*n_state, il*M*ggml_element_size(model.memory_cross_k)*n_state),
+                        ggml_view_1d(ctxL, model.memory_cross_k, M*n_state, offset_k + il*M*ggml_element_size(model.memory_cross_k)*n_state),
                         n_state/n_head, n_head, M);
 
             struct ggml_tensor * Vcross =
                 ggml_reshape_3d(ctxL,
-                        ggml_view_1d(ctxL, model.memory_cross_v, M*n_state, il*M*ggml_element_size(model.memory_cross_v)*n_state),
+                        ggml_view_1d(ctxL, model.memory_cross_v, M*n_state, offset_v + il*M*ggml_element_size(model.memory_cross_v)*n_state),
                         n_state/n_head, n_head, M);
 
             // ------
@@ -2116,7 +2126,26 @@ struct whisper_context * whisper_init(const char * path_model) {
 
     ctx->t_start_us = t_start_us;
 
-    if (!whisper_model_load(path_model, *ctx)) {
+    if (!whisper_model_load(path_model, 1, *ctx)) {
+        fprintf(stderr, "%s: failed to load model from '%s'\n", __func__, path_model);
+        return NULL;
+    }
+
+    ctx->t_load_us = ggml_time_us() - t_start_us;
+
+    return ctx;
+}
+
+struct whisper_context * whisper_init_parallel(const char * path_model, int n_processors) {
+    ggml_time_init();
+
+    whisper_context * ctx = new whisper_context;
+
+    const int64_t t_start_us = ggml_time_us();
+
+    ctx->t_start_us = t_start_us;
+
+    if (!whisper_model_load(path_model, n_processors, *ctx)) {
         fprintf(stderr, "%s: failed to load model from '%s'\n", __func__, path_model);
         return NULL;
     }
@@ -2167,7 +2196,7 @@ int whisper_set_mel(
 int whisper_encode(struct whisper_context * ctx, int offset, int n_threads) {
     const int64_t t_start_us = ggml_time_us();
 
-    if (!whisper_encode(*ctx, n_threads, offset)) {
+    if (!whisper_encode(*ctx, n_threads, offset, 0)) {
         fprintf(stderr, "%s: failed to eval\n", __func__);
         return -1;
     }
@@ -2180,7 +2209,7 @@ int whisper_encode(struct whisper_context * ctx, int offset, int n_threads) {
 int whisper_decode(struct whisper_context * ctx, const whisper_token * tokens, int n_tokens, int n_past, int n_threads) {
     const int64_t t_start_us = ggml_time_us();
 
-    if (!whisper_decode(*ctx, n_threads, tokens, n_tokens, n_past)) {
+    if (!whisper_decode(*ctx, n_threads, tokens, n_tokens, n_past, 0)) {
         fprintf(stderr, "%s: failed to eval\n", __func__);
         return 1;
     }
@@ -2302,6 +2331,7 @@ struct whisper_full_params whisper_full_default_params(enum whisper_sampling_str
 
                     /*.n_threads            =*/ std::min(4, (int32_t) std::thread::hardware_concurrency()),
                     /*.offset_ms            =*/ 0,
+                    /*.n_processors         =*/ 1,
 
                     /*.translate            =*/ false,
                     /*.no_context           =*/ false,
@@ -2333,6 +2363,7 @@ struct whisper_full_params whisper_full_default_params(enum whisper_sampling_str
 
                     /*.n_threads            =*/ std::min(4, (int32_t) std::thread::hardware_concurrency()),
                     /*.offset_ms            =*/ 0,
+                    /*.n_processors         =*/ 1,
 
                     /*.translate            =*/ false,
                     /*.no_context           =*/ false,
@@ -2369,7 +2400,6 @@ int whisper_full(
         int n_samples) {
     // clear old results
     auto & result_all = ctx->result_all;
-    auto & tokens_cur = ctx->tokens_cur;
 
     result_all.clear();
 
@@ -2379,10 +2409,12 @@ int whisper_full(
         return -1;
     }
 
+    const int seek_start = params.offset_ms/10;
+
     // if length of spectrogram is less than 1s (100 samples), then return
     // basically don't process anything that is less than 1s
     // see issue #39: https://github.com/ggerganov/whisper.cpp/issues/39
-    if (whisper_n_len(ctx) < 100) {
+    if (whisper_n_len(ctx) < 100 + seek_start) {
         return 0;
     }
 
@@ -2406,8 +2438,14 @@ int whisper_full(
     int progress_prev = 0;
     int progress_step = 5;
 
+    std::vector<whisper_token_data> tokens_cur;
+    tokens_cur.reserve(whisper_n_text_ctx(ctx));
+
+    std::vector<whisper_token> prompt;
+    prompt.reserve(whisper_n_text_ctx(ctx));
+
     // main loop
-    int seek = params.offset_ms/10;
+    int seek = seek_start;
     while (true) {
         int progress_cur = (100*seek)/whisper_n_len(ctx);
         while (progress_cur >= progress_prev + progress_step) {
@@ -2427,9 +2465,8 @@ int whisper_full(
             return 7;
         }
 
-        std::vector<whisper_token> prompt;
-
         int n_past = 0;
+        prompt.clear();
 
         // if we have already generated some text, use it as a prompt to condition the next generation
         if (prompt_past.size() > 0) {
diff --git a/whisper.h b/whisper.h
index 5414248..c918e98 100644
--- a/whisper.h
+++ b/whisper.h
@@ -72,6 +72,8 @@ extern "C" {
     // Returns NULL on failure.
     WHISPER_API struct whisper_context * whisper_init(const char * path_model);
 
+    WHISPER_API struct whisper_context * whisper_init_parallel(const char * path_model, int n_processors);
+
     // Frees all memory allocated by the model.
     WHISPER_API void whisper_free(struct whisper_context * ctx);
 
@@ -170,6 +172,7 @@ extern "C" {
 
         int n_threads;
         int offset_ms;
+        int n_processors;
 
         bool translate;
         bool no_context;