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All estimates are approximations based on mathematical models and public specifications. Actual performance may vary. Do not make purchasing decisions based solely on these estimates.

Data sourced from Hugging Face, Ollama, and official model documentation. Model names and logos are trademarks of their respective owners.

© 2026 Will It Run AI — Fase Consulting Ibiza, S.L. (NIF: B57969656)

Home/Devstral 2 123B Instruct/on NVIDIA H200 141GB

Can it run?

Can NVIDIA H200 141GB run Devstral 2 123B Instruct?

BGood

Runs well

Using Q4_K_M in vLLM

Capabilities:

Fit status

Runs well

Decode

53.7 tok/s

TTFT

3603 ms

Safe context

20K

Memory

110.7 GB / 141.0 GB

Memory breakdown

Weights75.0 GB
KV Cache19.2 GB
Runtime2.4 GB
Headroom14.1 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingCTight fit53.7 tok/s5240 ms35K
ChatBRuns well53.7 tok/s1965 ms11K
CodingBRuns well53.7 tok/s3603 ms20K
RAGCTight fit53.7 tok/s6550 ms35K
ReasoningBRuns well53.7 tok/s4258 ms20K

Quantization options

How Devstral 2 123B Instruct (123B params) fits at each quantization level on NVIDIA H200 141GB (141.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
48.0 GB
LowD37
Q3_K_S
3
60.3 GB
LowD39
NVFP4
4
68.9 GB
MediumC40
Q4_K_M
4
75.0 GB
MediumC41
Q5_K_M
5
88.6 GB
HighC43
Q6_KBest for your GPU
6
100.9 GB
HighC45
Q8_0
8
131.6 GB
Very HighC45
F16
16
252.2 GB
MaximumF0

Get started

HuggingFace
huggingface-cli download devstral-2-123b

Upgrade options

Hardware that runs Devstral 2 123B Instruct well

NVIDIANVIDIA B200 180GBBudget pick
B89.6 tok/s decode

~$30,000 MSRP

See all results for NVIDIA H200 141GBSee all hardware for Devstral 2 123B Instruct