Leanstral 119B A6B needs ~87.4 GB VRAM. RTX PRO 6000 Blackwell Workstation Edition 96GB has 96.0 GB. With NVFP4 quantization, expect ~52 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Too heavy
Decode
45.9 tok/s
TTFT
4222 ms
Safe context
21K
Memory
93.4 GB / 96.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Tight fit | 45.9 tok/s | 2303 ms | 21K |
| Coding | F | Too heavy | 45.9 tok/s | 4222 ms | 21K |
| Agentic Coding | F | Too heavy | 30.9 tok/s | 9119 ms | 21K |
| Reasoning | F | Too heavy | 45.9 tok/s | 4990 ms | 21K |
| RAG | F | Too heavy | 30.9 tok/s | 11398 ms | 21K |
Inference speed
Estimated decode speed (tokens/sec) for Leanstral 119B A6B at Q4_K_M across popular GPUs and Apple Silicon, including multi-GPU rigs, using the fastest local runtime per device. Fastest is Mac Studio M3 Ultra 256GB at ~17 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 17.0 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 11.9 | Too big |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 11.3 | Too big |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 8.8 | Too big |
2× RX 7900 XTX 24GB | 48 GB | Q4_K_M | 7.4 | Too big |
 2× RTX 4090 24GB | 48 GB | Q4_K_M | 6.7 | Too big |
| 2× RTX 3090 24GB | 48 GB | Q4_K_M | 5.8 | Too big |
| RTX 5090 32GB | 32 GB | Q4_K_M | 5.5 | Too big |
| 4× RTX 3060 12GB | 48 GB | Q4_K_M | 5.1 | Too big |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 3.7 | Too big |
| RTX 4090 24GB | 24 GB | Q4_K_M | 3.5 | Too big |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 3.2 | Too big |
| RTX 3090 24GB | 24 GB | Q4_K_M | 3.0 | Too big |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 2.8 | Too big |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 2.6 | Too big |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 2.4 | Too big |
| RTX 4070 12GB | 12 GB | Q4_K_M | 2.0 | Too big |
| RTX 3060 12GB | 12 GB | Q4_K_M | 2.0 | Too big |
| RTX 4060 8GB | 8 GB | Q4_K_M | 2.0 | Too big |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 2.0 | Too big |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How Leanstral 119B A6B (119B params) fits at each quantization level on RTX PRO 6000 Blackwell Workstation Edition 96GB (96.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 46.4 GB | Low | A83 |
Q3_K_S | 3 | 58.3 GB | Low | A84 |
NVFP4 | 4 | 66.6 GB | Medium | A84 |
Q4_K_MBest for your GPU | 4 | 72.6 GB | Medium | A84 |
Q5_K_M | 5 | 85.7 GB | High | F0 |
Q6_K | 6 | 97.6 GB | High | F0 |
Q8_0 | 8 | 127.3 GB | Very High | F0 |
F16 | 16 | 244.0 GB | Maximum | F0 |
Copy-paste commands to run Leanstral 119B A6B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "mistralai/Leanstral-2603" \
--hf-file "Leanstral-2603-Q4_K_M.gguf" \
-c 4096 -ngl 99Upgrade options
NVIDIA H200 141GBBudget pickMakes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 93%.
~$30,000 MSRP
NVIDIA H200 PCIe 141GBBest valueMakes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 93%.
~$30,000 MSRP
NVIDIA B200 180GBNVIDIA upgradeMakes the model fit on the accelerator instead of staying completely out of reach.
Raises estimated decode speed by about 346%.
~$30,000 MSRP
Yes, RTX PRO 6000 Blackwell Workstation Edition 96GB can run Leanstral 119B A6B at NVFP4 quantization (Tight fit). The recommended Q4_K_M requires 93.4 GB which exceeds available memory, but at NVFP4 it needs only 87.4 GB. Expected decode speed: 52.4 tok/s.
Leanstral 119B A6B (119B parameters) requires approximately 93.4 GB at Q4_K_M quantization. On RTX PRO 6000 Blackwell Workstation Edition 96GB, it fits at NVFP4 using 87.4 GB.
The recommended quantization is Q4_K_M, but on RTX PRO 6000 Blackwell Workstation Edition 96GB the best fitting quantization is NVFP4, which uses 87.4 GB.
On RTX PRO 6000 Blackwell Workstation Edition 96GB, Leanstral 119B A6B achieves approximately 52.4 tokens per second decode speed with a time-to-first-token of 3691ms using NVFP4 quantization.
For coding workloads, Leanstral 119B A6B on RTX PRO 6000 Blackwell Workstation Edition 96GB receives a F grade with 45.9 tok/s and 21K context.
On RTX PRO 6000 Blackwell Workstation Edition 96GB, Leanstral 119B A6B can safely use up to 32K tokens of context at NVFP4 quantization. The model's official context limit is 256K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
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