mistralrs tune
Recommend quantization + device mapping for a model. Rejects --quant auto; pass --quant <level> or --isq <level> to bias the recommendation toward a specific quantization target
mistralrs tune [OPTIONS] [COMMAND]| Option | Default | Description |
|---|---|---|
-m, --model-id <MODEL_ID> | HuggingFace model ID or local path to model directory | |
-t, --tokenizer <TOKENIZER> | Path to local tokenizer.json file | |
-a, --arch <ARCH> | Model architecture (auto-detected if not specified) | |
--dtype <DTYPE> | auto | Model data type |
--format <FORMAT> | Model format: plain (safetensors), gguf, or ggml Auto-detected if not specified Possible values: plain, gguf, ggml. | |
-f, --quantized-file <QUANTIZED_FILE> | Quantized model filename(s) for GGUF/GGML (semicolon-separated for multiple) | |
--tok-model-id <TOK_MODEL_ID> | Model ID for tokenizer when using quantized format | |
--gqa <GQA> | 1 | GQA value for GGML models |
--lora <LORA> | LoRA adapter model ID(s), semicolon-separated for multiple | |
--xlora <XLORA> | X-LoRA adapter model ID | |
--xlora-order <XLORA_ORDER> | X-LoRA ordering JSON file | |
--tgt-non-granular-index <TGT_NON_GRANULAR_INDEX> | Target non-granular index for X-LoRA | |
--quant <QUANT> | Quantization front-door. Numeric levels (2, 3, 4, 5, 6, 8) and ISQ names prefer a prebuilt UQFF from mistralrs-community/<model>-UQFF, then fall back to ISQ. auto is for serve, run, and bench; tune rejects it because tune is the recommender. Use --isq for the explicit knob | |
--isq <IN_SITU_QUANT> | In-situ quantization level (e.g., “4”, “8”, “q4_0”, “q4_1”, etc.) | |
--from-uqff <FROM_UQFF> | UQFF file(s) to load from. Accepts numeric shorthands (2, 3, 4, 5, 6, 8) to auto-detect the appropriate UQFF file (e.g., --from-uqff 8 finds q8_0-0.uqff or afq8-0.uqff). Also accepts ISQ type names (e.g., q4k, afq8). Shards are auto-discovered: specifying the first shard (e.g., q4k-0.uqff) automatically finds q4k-1.uqff, etc. Use semicolons to separate different quantizations | |
--isq-organization <ISQ_ORGANIZATION> | ISQ organization strategy: default or moqe | |
--imatrix <IMATRIX> | imatrix file for enhanced quantization | |
--calibration-file <CALIBRATION_FILE> | Calibration file for imatrix generation | |
--cpu | false | Force CPU-only execution |
-n, --device-layers <DEVICE_LAYERS> | Device layer mapping (format: ORD:NUM;… e.g., “0:10;1:20”) Omit for automatic device mapping | |
--topology <TOPOLOGY> | Topology YAML file for device mapping | |
--hf-cache <HF_CACHE> | Custom HuggingFace cache directory | |
--max-seq-len <MAX_SEQ_LEN> | 4096 | Max sequence length for automatic device mapping |
--max-batch-size <MAX_BATCH_SIZE> | 1 | Max batch size for automatic device mapping |
--paged-attn <MODE> | auto | PagedAttention mode - auto: enabled on CUDA, disabled on Metal/CPU (default) - on: force enable (fails if unsupported) - off: force disable Possible values: auto, on, off. |
--pa-context-len <CONTEXT_LEN> | Allocate KV cache for this context length. If not specified, defaults to using 90% of available VRAM | |
--pa-memory-mb <MEMORY_MB> | GPU memory to allocate in MBs (alternative to context-len) | |
--pa-memory-fraction <MEMORY_FRACTION> | GPU memory utilization fraction 0.0-1.0 (alternative to context-len/memory-mb) | |
--pa-block-size <BLOCK_SIZE> | Tokens per block (default: 32 on CUDA) | |
--pa-cache-type <CACHE_TYPE> | auto | KV cache quantization type |
--max-edge <MAX_EDGE> | Maximum edge length for image resizing (aspect ratio preserved) | |
--max-num-images <MAX_NUM_IMAGES> | Maximum number of images per request | |
--max-image-length <MAX_IMAGE_LENGTH> | Maximum image dimension for device mapping | |
--profile <PROFILE> | balanced | Tuning profile (quality, balanced, fast) Possible values: quality, balanced, fast. |
--json | false | Output JSON instead of human-readable text |
--emit-config <EMIT_CONFIG> | Emit a TOML config file with the recommended settings |
mistralrs tune auto
Section titled “mistralrs tune auto”Auto-detect model type (recommended)
mistralrs tune auto [OPTIONS] --model-id <MODEL_ID>| Option | Default | Description |
|---|---|---|
-m, --model-id <MODEL_ID> | required | HuggingFace model ID or local path to model directory |
-t, --tokenizer <TOKENIZER> | Path to local tokenizer.json file | |
-a, --arch <ARCH> | Model architecture (auto-detected if not specified) | |
--dtype <DTYPE> | auto | Model data type |
--format <FORMAT> | Model format: plain (safetensors), gguf, or ggml Auto-detected if not specified Possible values: plain, gguf, ggml. | |
-f, --quantized-file <QUANTIZED_FILE> | Quantized model filename(s) for GGUF/GGML (semicolon-separated for multiple) | |
--tok-model-id <TOK_MODEL_ID> | Model ID for tokenizer when using quantized format | |
--gqa <GQA> | 1 | GQA value for GGML models |
--lora <LORA> | LoRA adapter model ID(s), semicolon-separated for multiple | |
--xlora <XLORA> | X-LoRA adapter model ID | |
--xlora-order <XLORA_ORDER> | X-LoRA ordering JSON file | |
--tgt-non-granular-index <TGT_NON_GRANULAR_INDEX> | Target non-granular index for X-LoRA | |
--quant <QUANT> | Quantization front-door. Numeric levels (2, 3, 4, 5, 6, 8) and ISQ names prefer a prebuilt UQFF from mistralrs-community/<model>-UQFF, then fall back to ISQ. auto is for serve, run, and bench; tune rejects it because tune is the recommender. Use --isq for the explicit knob | |
--isq <IN_SITU_QUANT> | In-situ quantization level (e.g., “4”, “8”, “q4_0”, “q4_1”, etc.) | |
--from-uqff <FROM_UQFF> | UQFF file(s) to load from. Accepts numeric shorthands (2, 3, 4, 5, 6, 8) to auto-detect the appropriate UQFF file (e.g., --from-uqff 8 finds q8_0-0.uqff or afq8-0.uqff). Also accepts ISQ type names (e.g., q4k, afq8). Shards are auto-discovered: specifying the first shard (e.g., q4k-0.uqff) automatically finds q4k-1.uqff, etc. Use semicolons to separate different quantizations | |
--isq-organization <ISQ_ORGANIZATION> | ISQ organization strategy: default or moqe | |
--imatrix <IMATRIX> | imatrix file for enhanced quantization | |
--calibration-file <CALIBRATION_FILE> | Calibration file for imatrix generation | |
--cpu | false | Force CPU-only execution |
-n, --device-layers <DEVICE_LAYERS> | Device layer mapping (format: ORD:NUM;… e.g., “0:10;1:20”) Omit for automatic device mapping | |
--topology <TOPOLOGY> | Topology YAML file for device mapping | |
--hf-cache <HF_CACHE> | Custom HuggingFace cache directory | |
--max-seq-len <MAX_SEQ_LEN> | 4096 | Max sequence length for automatic device mapping |
--max-batch-size <MAX_BATCH_SIZE> | 1 | Max batch size for automatic device mapping |
--paged-attn <MODE> | auto | PagedAttention mode - auto: enabled on CUDA, disabled on Metal/CPU (default) - on: force enable (fails if unsupported) - off: force disable Possible values: auto, on, off. |
--pa-context-len <CONTEXT_LEN> | Allocate KV cache for this context length. If not specified, defaults to using 90% of available VRAM | |
--pa-memory-mb <MEMORY_MB> | GPU memory to allocate in MBs (alternative to context-len) | |
--pa-memory-fraction <MEMORY_FRACTION> | GPU memory utilization fraction 0.0-1.0 (alternative to context-len/memory-mb) | |
--pa-block-size <BLOCK_SIZE> | Tokens per block (default: 32 on CUDA) | |
--pa-cache-type <CACHE_TYPE> | auto | KV cache quantization type |
--max-edge <MAX_EDGE> | Maximum edge length for image resizing (aspect ratio preserved) | |
--max-num-images <MAX_NUM_IMAGES> | Maximum number of images per request | |
--max-image-length <MAX_IMAGE_LENGTH> | Maximum image dimension for device mapping |
mistralrs tune text
Section titled “mistralrs tune text”Text generation model with explicit configuration
mistralrs tune text [OPTIONS] --model-id <MODEL_ID>| Option | Default | Description |
|---|---|---|
-m, --model-id <MODEL_ID> | required | HuggingFace model ID or local path to model directory |
-t, --tokenizer <TOKENIZER> | Path to local tokenizer.json file | |
-a, --arch <ARCH> | Model architecture (auto-detected if not specified) | |
--dtype <DTYPE> | auto | Model data type |
--format <FORMAT> | Model format: plain (safetensors), gguf, or ggml Auto-detected if not specified Possible values: plain, gguf, ggml. | |
-f, --quantized-file <QUANTIZED_FILE> | Quantized model filename(s) for GGUF/GGML (semicolon-separated for multiple) | |
--tok-model-id <TOK_MODEL_ID> | Model ID for tokenizer when using quantized format | |
--gqa <GQA> | 1 | GQA value for GGML models |
--lora <LORA> | LoRA adapter model ID(s), semicolon-separated for multiple | |
--xlora <XLORA> | X-LoRA adapter model ID | |
--xlora-order <XLORA_ORDER> | X-LoRA ordering JSON file | |
--tgt-non-granular-index <TGT_NON_GRANULAR_INDEX> | Target non-granular index for X-LoRA | |
--quant <QUANT> | Quantization front-door. Numeric levels (2, 3, 4, 5, 6, 8) and ISQ names prefer a prebuilt UQFF from mistralrs-community/<model>-UQFF, then fall back to ISQ. auto is for serve, run, and bench; tune rejects it because tune is the recommender. Use --isq for the explicit knob | |
--isq <IN_SITU_QUANT> | In-situ quantization level (e.g., “4”, “8”, “q4_0”, “q4_1”, etc.) | |
--from-uqff <FROM_UQFF> | UQFF file(s) to load from. Accepts numeric shorthands (2, 3, 4, 5, 6, 8) to auto-detect the appropriate UQFF file (e.g., --from-uqff 8 finds q8_0-0.uqff or afq8-0.uqff). Also accepts ISQ type names (e.g., q4k, afq8). Shards are auto-discovered: specifying the first shard (e.g., q4k-0.uqff) automatically finds q4k-1.uqff, etc. Use semicolons to separate different quantizations | |
--isq-organization <ISQ_ORGANIZATION> | ISQ organization strategy: default or moqe | |
--imatrix <IMATRIX> | imatrix file for enhanced quantization | |
--calibration-file <CALIBRATION_FILE> | Calibration file for imatrix generation | |
--cpu | false | Force CPU-only execution |
-n, --device-layers <DEVICE_LAYERS> | Device layer mapping (format: ORD:NUM;… e.g., “0:10;1:20”) Omit for automatic device mapping | |
--topology <TOPOLOGY> | Topology YAML file for device mapping | |
--hf-cache <HF_CACHE> | Custom HuggingFace cache directory | |
--max-seq-len <MAX_SEQ_LEN> | 4096 | Max sequence length for automatic device mapping |
--max-batch-size <MAX_BATCH_SIZE> | 1 | Max batch size for automatic device mapping |
--paged-attn <MODE> | auto | PagedAttention mode - auto: enabled on CUDA, disabled on Metal/CPU (default) - on: force enable (fails if unsupported) - off: force disable Possible values: auto, on, off. |
--pa-context-len <CONTEXT_LEN> | Allocate KV cache for this context length. If not specified, defaults to using 90% of available VRAM | |
--pa-memory-mb <MEMORY_MB> | GPU memory to allocate in MBs (alternative to context-len) | |
--pa-memory-fraction <MEMORY_FRACTION> | GPU memory utilization fraction 0.0-1.0 (alternative to context-len/memory-mb) | |
--pa-block-size <BLOCK_SIZE> | Tokens per block (default: 32 on CUDA) | |
--pa-cache-type <CACHE_TYPE> | auto | KV cache quantization type |
mistralrs tune multimodal
Section titled “mistralrs tune multimodal”Multimodal model
mistralrs tune multimodal [OPTIONS] --model-id <MODEL_ID>| Option | Default | Description |
|---|---|---|
-m, --model-id <MODEL_ID> | required | HuggingFace model ID or local path to model directory |
-t, --tokenizer <TOKENIZER> | Path to local tokenizer.json file | |
-a, --arch <ARCH> | Model architecture (auto-detected if not specified) | |
--dtype <DTYPE> | auto | Model data type |
--format <FORMAT> | Model format: plain (safetensors), gguf, or ggml Auto-detected if not specified Possible values: plain, gguf, ggml. | |
-f, --quantized-file <QUANTIZED_FILE> | Quantized model filename(s) for GGUF/GGML (semicolon-separated for multiple) | |
--tok-model-id <TOK_MODEL_ID> | Model ID for tokenizer when using quantized format | |
--gqa <GQA> | 1 | GQA value for GGML models |
--lora <LORA> | LoRA adapter model ID(s), semicolon-separated for multiple | |
--xlora <XLORA> | X-LoRA adapter model ID | |
--xlora-order <XLORA_ORDER> | X-LoRA ordering JSON file | |
--tgt-non-granular-index <TGT_NON_GRANULAR_INDEX> | Target non-granular index for X-LoRA | |
--quant <QUANT> | Quantization front-door. Numeric levels (2, 3, 4, 5, 6, 8) and ISQ names prefer a prebuilt UQFF from mistralrs-community/<model>-UQFF, then fall back to ISQ. auto is for serve, run, and bench; tune rejects it because tune is the recommender. Use --isq for the explicit knob | |
--isq <IN_SITU_QUANT> | In-situ quantization level (e.g., “4”, “8”, “q4_0”, “q4_1”, etc.) | |
--from-uqff <FROM_UQFF> | UQFF file(s) to load from. Accepts numeric shorthands (2, 3, 4, 5, 6, 8) to auto-detect the appropriate UQFF file (e.g., --from-uqff 8 finds q8_0-0.uqff or afq8-0.uqff). Also accepts ISQ type names (e.g., q4k, afq8). Shards are auto-discovered: specifying the first shard (e.g., q4k-0.uqff) automatically finds q4k-1.uqff, etc. Use semicolons to separate different quantizations | |
--isq-organization <ISQ_ORGANIZATION> | ISQ organization strategy: default or moqe | |
--imatrix <IMATRIX> | imatrix file for enhanced quantization | |
--calibration-file <CALIBRATION_FILE> | Calibration file for imatrix generation | |
--cpu | false | Force CPU-only execution |
-n, --device-layers <DEVICE_LAYERS> | Device layer mapping (format: ORD:NUM;… e.g., “0:10;1:20”) Omit for automatic device mapping | |
--topology <TOPOLOGY> | Topology YAML file for device mapping | |
--hf-cache <HF_CACHE> | Custom HuggingFace cache directory | |
--max-seq-len <MAX_SEQ_LEN> | 4096 | Max sequence length for automatic device mapping |
--max-batch-size <MAX_BATCH_SIZE> | 1 | Max batch size for automatic device mapping |
--paged-attn <MODE> | auto | PagedAttention mode - auto: enabled on CUDA, disabled on Metal/CPU (default) - on: force enable (fails if unsupported) - off: force disable Possible values: auto, on, off. |
--pa-context-len <CONTEXT_LEN> | Allocate KV cache for this context length. If not specified, defaults to using 90% of available VRAM | |
--pa-memory-mb <MEMORY_MB> | GPU memory to allocate in MBs (alternative to context-len) | |
--pa-memory-fraction <MEMORY_FRACTION> | GPU memory utilization fraction 0.0-1.0 (alternative to context-len/memory-mb) | |
--pa-block-size <BLOCK_SIZE> | Tokens per block (default: 32 on CUDA) | |
--pa-cache-type <CACHE_TYPE> | auto | KV cache quantization type |
--max-edge <MAX_EDGE> | Maximum edge length for image resizing (aspect ratio preserved) | |
--max-num-images <MAX_NUM_IMAGES> | Maximum number of images per request | |
--max-image-length <MAX_IMAGE_LENGTH> | Maximum image dimension for device mapping |
mistralrs tune diffusion
Section titled “mistralrs tune diffusion”Image generation model (diffusion)
mistralrs tune diffusion [OPTIONS] --model-id <MODEL_ID>| Option | Default | Description |
|---|---|---|
-m, --model-id <MODEL_ID> | required | HuggingFace model ID or local path to model directory |
-t, --tokenizer <TOKENIZER> | Path to local tokenizer.json file | |
-a, --arch <ARCH> | Model architecture (auto-detected if not specified) | |
--dtype <DTYPE> | auto | Model data type |
--cpu | false | Force CPU-only execution |
-n, --device-layers <DEVICE_LAYERS> | Device layer mapping (format: ORD:NUM;… e.g., “0:10;1:20”) Omit for automatic device mapping | |
--topology <TOPOLOGY> | Topology YAML file for device mapping | |
--hf-cache <HF_CACHE> | Custom HuggingFace cache directory | |
--max-seq-len <MAX_SEQ_LEN> | 4096 | Max sequence length for automatic device mapping |
--max-batch-size <MAX_BATCH_SIZE> | 1 | Max batch size for automatic device mapping |
mistralrs tune speech
Section titled “mistralrs tune speech”Speech synthesis model
mistralrs tune speech [OPTIONS] --model-id <MODEL_ID>| Option | Default | Description |
|---|---|---|
-m, --model-id <MODEL_ID> | required | HuggingFace model ID or local path to model directory |
-t, --tokenizer <TOKENIZER> | Path to local tokenizer.json file | |
-a, --arch <ARCH> | Model architecture (auto-detected if not specified) | |
--dtype <DTYPE> | auto | Model data type |
--cpu | false | Force CPU-only execution |
-n, --device-layers <DEVICE_LAYERS> | Device layer mapping (format: ORD:NUM;… e.g., “0:10;1:20”) Omit for automatic device mapping | |
--topology <TOPOLOGY> | Topology YAML file for device mapping | |
--hf-cache <HF_CACHE> | Custom HuggingFace cache directory | |
--max-seq-len <MAX_SEQ_LEN> | 4096 | Max sequence length for automatic device mapping |
--max-batch-size <MAX_BATCH_SIZE> | 1 | Max batch size for automatic device mapping |
mistralrs tune embedding
Section titled “mistralrs tune embedding”Embedding model
mistralrs tune embedding [OPTIONS] --model-id <MODEL_ID>| Option | Default | Description |
|---|---|---|
-m, --model-id <MODEL_ID> | required | HuggingFace model ID or local path to model directory |
-t, --tokenizer <TOKENIZER> | Path to local tokenizer.json file | |
-a, --arch <ARCH> | Model architecture (auto-detected if not specified) | |
--dtype <DTYPE> | auto | Model data type |
--format <FORMAT> | Model format: plain (safetensors), gguf, or ggml Auto-detected if not specified Possible values: plain, gguf, ggml. | |
-f, --quantized-file <QUANTIZED_FILE> | Quantized model filename(s) for GGUF/GGML (semicolon-separated for multiple) | |
--tok-model-id <TOK_MODEL_ID> | Model ID for tokenizer when using quantized format | |
--gqa <GQA> | 1 | GQA value for GGML models |
--quant <QUANT> | Quantization front-door. Numeric levels (2, 3, 4, 5, 6, 8) and ISQ names prefer a prebuilt UQFF from mistralrs-community/<model>-UQFF, then fall back to ISQ. auto is for serve, run, and bench; tune rejects it because tune is the recommender. Use --isq for the explicit knob | |
--isq <IN_SITU_QUANT> | In-situ quantization level (e.g., “4”, “8”, “q4_0”, “q4_1”, etc.) | |
--from-uqff <FROM_UQFF> | UQFF file(s) to load from. Accepts numeric shorthands (2, 3, 4, 5, 6, 8) to auto-detect the appropriate UQFF file (e.g., --from-uqff 8 finds q8_0-0.uqff or afq8-0.uqff). Also accepts ISQ type names (e.g., q4k, afq8). Shards are auto-discovered: specifying the first shard (e.g., q4k-0.uqff) automatically finds q4k-1.uqff, etc. Use semicolons to separate different quantizations | |
--isq-organization <ISQ_ORGANIZATION> | ISQ organization strategy: default or moqe | |
--imatrix <IMATRIX> | imatrix file for enhanced quantization | |
--calibration-file <CALIBRATION_FILE> | Calibration file for imatrix generation | |
--cpu | false | Force CPU-only execution |
-n, --device-layers <DEVICE_LAYERS> | Device layer mapping (format: ORD:NUM;… e.g., “0:10;1:20”) Omit for automatic device mapping | |
--topology <TOPOLOGY> | Topology YAML file for device mapping | |
--hf-cache <HF_CACHE> | Custom HuggingFace cache directory | |
--max-seq-len <MAX_SEQ_LEN> | 4096 | Max sequence length for automatic device mapping |
--max-batch-size <MAX_BATCH_SIZE> | 1 | Max batch size for automatic device mapping |
--paged-attn <MODE> | auto | PagedAttention mode - auto: enabled on CUDA, disabled on Metal/CPU (default) - on: force enable (fails if unsupported) - off: force disable Possible values: auto, on, off. |
--pa-context-len <CONTEXT_LEN> | Allocate KV cache for this context length. If not specified, defaults to using 90% of available VRAM | |
--pa-memory-mb <MEMORY_MB> | GPU memory to allocate in MBs (alternative to context-len) | |
--pa-memory-fraction <MEMORY_FRACTION> | GPU memory utilization fraction 0.0-1.0 (alternative to context-len/memory-mb) | |
--pa-block-size <BLOCK_SIZE> | Tokens per block (default: 32 on CUDA) | |
--pa-cache-type <CACHE_TYPE> | auto | KV cache quantization type |