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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 RTX A6000 48GB

Can it run?

Can RTX A6000 48GB run Devstral 2 123B Instruct?

FWon't run

Too heavy

Using Q4_K_M in vLLM

Capabilities:

Fit status

Too heavy

Decode

7.8 tok/s

TTFT

24887 ms

Safe context

8K

Memory

101.4 GB / 48.0 GB

Memory breakdown

Weights75.0 GB
KV Cache19.2 GB
Runtime2.4 GB
Headroom4.8 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingFToo heavy7.8 tok/s36199 ms13K
ChatFToo heavy7.8 tok/s13575 ms4K
CodingFToo heavy7.8 tok/s24887 ms8K
RAGFToo heavy7.8 tok/s45248 ms13K
ReasoningFToo heavy7.8 tok/s29411 ms8K

Quantization options

How Devstral 2 123B Instruct (123B params) fits at each quantization level on RTX A6000 48GB (48.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
48.0 GB
LowC45
Q3_K_S
3
60.3 GB
LowF0
NVFP4
4
68.9 GB
MediumF0
Q4_K_M
4
75.0 GB
MediumF0
Q5_K_M
5
88.6 GB
HighF0
Q6_K
6
100.9 GB
HighF0
Q8_0
8
131.6 GB
Very HighF0
F16
16
252.2 GB
MaximumF0

Upgrade options

Hardware that runs Devstral 2 123B Instruct well

AppleMacBook Pro M3 Max 128GBBest value
D3 tok/s decode

~$2,499 MSRP

AMDAMD Instinct MI350X 288GBBudget pick
C77.8 tok/s decode

~$8,000 MSRP

NVIDIANVIDIA B200 180GBBiggest leap
B89.6 tok/s decode

~$30,000 MSRP

NVIDIANVIDIA H200 141GBNVIDIA upgrade
B53.7 tok/s decode

~$30,000 MSRP

See all results for RTX A6000 48GBSee all hardware for Devstral 2 123B Instruct