Can Command R 35B run on AMD Instinct MI250X 128GB?

YES — Runs Great

A74Great
Estimated from fit model

Command R 35B needs ~37.5 GB VRAM. AMD Instinct MI250X 128GB has 128.0 GB. With Q4_K_M quantization, expect ~127 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: Balanced
Share:

Operating mode

Choose the run profile you care about

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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) 37.5 GB, 127.1 tok/s, Runs well
37.5 GB required128.0 GB available
29% VRAM used

Fit status

Runs well

Decode

127.1 tok/s

TTFT

1523 ms

Safe context

131K

Memory

37.5 GB / 128.0 GB

Memory breakdown

Weights21.3 GB
KV Cache2.4 GB
Runtime0.9 GB
Headroom12.8 GB

See how fast it feels

See how fast it feelsCommand R 35B on AMD Instinct MI250X 128GB
1st promptCold start — includes initialization
>What is local AI inference?
Local AI inference means running an AI language model directly on your own hardware — your laptop, desktop, or server — instead of sending requests to a remote cloud API. When you run inference locally the model weights are loaded into your GPU or unified memory. Each token you generate requires reading those weights from memory, so memory bandwidth is the main bottleneck for decode speed. Key benefits of running locally: - Full privacy: your prompts never leave your machine - No per-token cost or rate limits - Works offline once the model is downloaded - Latency depends only on your hardware
2nd promptWarm — model ready, no init overhead
>How much VRAM do I need?
It depends on the model size and quantization level. A rough rule of thumb: Model size Q4 (4-bit) Q8 (8-bit) FP16 7B params ~4.3 GB ~7.5 GB ~14 GB 13B params ~7.9 GB ~13.9 GB ~26 GB 70B params ~42.7 GB ~74.9 GB ~140 GB Most people use 4-bit quantization (Q4_K_M) which gives 90-95% of full quality at a fraction of the memory. A 24 GB GPU can comfortably run most 7B-13B models.
Estimated: 127.1 tok/s decode · 1.5s TTFT (warm) · 318 tok/s prefill

What limits this setup

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.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns well127.1 tok/s831 ms131K
CodingARuns well127.1 tok/s1523 ms131K
Agentic CodingARuns well127.1 tok/s2215 ms131K
ReasoningARuns well127.1 tok/s1800 ms131K
RAGARuns well127.1 tok/s2769 ms131K

Inference speed

Command R 35B inference speed — tokens per second by GPU & Mac

Estimated decode speed (tokens/sec) for Command R 35B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~40 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 / MacMemoryQuantSpeed (tok/s)Fits?
NVIDIARTX 5090 32GB
32 GBQ4_K_M39.6Tight
MacBook Pro M4 Max 128GB
128 GBQ4_K_M30.6Fits
MacBook Pro M4 Max 64GB
64 GBQ4_K_M30.6Fits
Mac Studio M3 Ultra 256GB
256 GBQ4_K_M28.4Fits
Mac Studio M2 Ultra 128GB
128 GBQ4_K_M23.6Fits
Mac Studio M1 Ultra 128GB
128 GBQ4_K_M22.4Fits
RX 7900 XTX 24GB
24 GBQ4_K_M20.5Heavy offload
MacBook Pro M4 Pro 48GB
48 GBQ4_K_M19.3Tight
NVIDIARTX 4090 24GB
24 GBQ4_K_M13.1Heavy offload
MacBook Pro M3 Max 64GB
64 GBQ4_K_M12.2Fits
NVIDIARTX 3090 24GB
24 GBQ4_K_M12.0Heavy offload
MacBook Pro M1 Max 64GB
64 GBQ4_K_M11.2Fits
NVIDIARTX 4080 Super 16GB
16 GBQ4_K_M4.7Too big
NVIDIARTX 4070 12GB
12 GBQ4_K_M2.0Too big
NVIDIARTX 3060 12GB
12 GBQ4_K_M2.0Too big
NVIDIARTX 4060 8GB
8 GBQ4_K_M2.0Too 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.

Quantization options

How Command R 35B (35B params) fits at each quantization level on AMD Instinct MI250X 128GB (128.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
13.7 GB
LowB65
Q3_K_S
3
17.2 GB
LowB65
NVFP4
4
19.6 GB
MediumB65
Q4_K_M
4
21.3 GB
MediumB66
Q5_K_M
5
25.2 GB
HighB66
Q6_K
6
28.7 GB
HighB67
Q8_0
8
37.5 GB
Very HighB68
F16Best for your GPU
16
71.8 GB
MaximumA74

Get started

Copy-paste commands to run Command R 35B on your machine.

Run

ollama run command-r

Your hardware

More models your AMD Instinct MI250X 128GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BS36.2 tok/s
AlibabaQwen 3.5 122B A10B122BS100.3 tok/s
MistralMistral Small 4 119B119BS108.8 tok/s
OpenAIGPT-OSS 120B117BS38 tok/s
CohereCommand A 111B111BS40.2 tok/s

Frequently asked questions

Can AMD Instinct MI250X 128GB run Command R 35B?

Yes, AMD Instinct MI250X 128GB can run Command R 35B with a A grade (Runs well). Expected decode speed: 127.1 tok/s.

How much VRAM does Command R 35B need?

Command R 35B (35B parameters) requires approximately 37.5 GB of memory with Q4_K_M quantization.

What is the best quantization for Command R 35B?

The recommended quantization for Command R 35B is Q4_K_M, which balances quality and memory efficiency.

What speed will Command R 35B run at on AMD Instinct MI250X 128GB?

On AMD Instinct MI250X 128GB, Command R 35B achieves approximately 127.1 tokens per second decode speed with a time-to-first-token of 1523ms using Q4_K_M quantization.

Can AMD Instinct MI250X 128GB run Command R 35B for coding?

For coding workloads, Command R 35B on AMD Instinct MI250X 128GB receives a A grade with 127.1 tok/s and 131K context.

What context window can Command R 35B use on AMD Instinct MI250X 128GB?

On AMD Instinct MI250X 128GB, Command R 35B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for AMD Instinct MI250X 128GBSee all hardware for Command R 35B
Embed this result

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/command-r-35b-on-instinct-mi250x-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: