Claude Fable 5$22.000/MClaude Opus 4.8$11.000/MClaude Opus 4.7$11.000/MClaude Opus 4.6$11.000/MClaude Opus 4.5$33.000/MClaude Sonnet 3.7$6.600/MClaude Opus 3$33.000/MClaude 2.1$12.800/MClaude 2$12.800/MGPT-5.5$12.500/MGPT-5.2$5.425/MGPT-5.2-Codex$5.425/MGPT-5$3.875/MGPT-4.5$97.500/MGPT-4 Turbo Preview$16.000/MGPT-4$39.000/MGPT-4-32k$78.000/Mo3$19.000/Mo3-mini$2.090/Mo4-mini$2.090/Mo1$28.500/Mo1-mini$5.700/Mo1-preview$28.500/MGemini 3.5 Pro$5.000/MGemini 3.1 Pro$5.000/MGemini 3 Pro$5.000/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/MClaude Fable 5$22.000/MClaude Opus 4.8$11.000/MClaude Opus 4.7$11.000/MClaude Opus 4.6$11.000/MClaude Opus 4.5$33.000/MClaude Sonnet 3.7$6.600/MClaude Opus 3$33.000/MClaude 2.1$12.800/MClaude 2$12.800/MGPT-5.5$12.500/MGPT-5.2$5.425/MGPT-5.2-Codex$5.425/MGPT-5$3.875/MGPT-4.5$97.500/MGPT-4 Turbo Preview$16.000/MGPT-4$39.000/MGPT-4-32k$78.000/Mo3$19.000/Mo3-mini$2.090/Mo4-mini$2.090/Mo1$28.500/Mo1-mini$5.700/Mo1-preview$28.500/MGemini 3.5 Pro$5.000/MGemini 3.1 Pro$5.000/MGemini 3 Pro$5.000/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/M
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Nvidia
NvidiaFrontier

Mistral-Large-2 (NIM)

Enterprise

Mistral Large 2 served via NVIDIA NIM. Identical Mistral weights with NVIDIA enterprise integration.

Mistral-Large-2 (NIM) is a frontier AI model from Nvidia. It costs $2.000 per million input tokens and $6.000 per million output tokens (blended $3.200/M), with a 128K-token context window.

Modalities textOfficial model page ↗API docs ↗Compare with another model →Estimate monthly cost →
INPUT
$2.000/M
per million input tokens
OUTPUT
$6.000/M
per million output tokens
BLENDED 70/30
$3.200/M
default reference rate · how it's calculated →
CONTEXT
128K
128,000 tokens
What it's good at
  • Mistral Large 2 quality
  • NIM enterprise packaging
  • On-prem NVIDIA hosting
Typical use cases
  • NVIDIA-stack frontier inference
  • On-prem large-model deployments
Benchmarks
vs. best public score
Scores inherited from Mistral Large 2 — this is a hosted variant of the same open-weights model, so the underlying benchmark scores are identical.
MMLU84%
Multitask academic knowledge across 57 subjects.
GPQA Diamond52%
Graduate-level science questions, "Google-proof".
MATH73%
High-school competition math problems.
HumanEval92%
Python function synthesis from docstrings.
LMArena Elo1283 Elo
Crowd-sourced head-to-head preference Elo rating.
Hand-curated from each provider's published reports and public leaderboards. Methodology varies across sources — treat as directional rather than authoritative.
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RLHF-Aligned · 128K ctx
in $0.350/Mout $0.400/M
Llama-3.1-Nemotron-Ultra-253B
Ultra · 128K ctx
in $1.600/Mout $1.600/M
Nemotron-4-340B
Large · 4K ctx
in $4.200/Mout $4.200/M
Mistral-NeMo-12B (NIM)
Efficient · 128K ctx
in $0.150/Mout $0.150/M
Phi-3-Mini-4K (NIM)
Nano · 4K ctx
in $0.040/Mout $0.040/M
Frequently asked questions

How much does Mistral-Large-2 (NIM) cost?

Mistral-Large-2 (NIM) costs $2.000 per million input tokens and $6.000 per million output tokens, for a blended reference rate of $3.200 per million tokens.

What is Mistral-Large-2 (NIM)'s context window?

Mistral-Large-2 (NIM) supports up to 128K tokens of context (128,000 tokens).

What is Mistral-Large-2 (NIM) best for?

Mistral-Large-2 (NIM) is well suited to Mistral Large 2 quality, NIM enterprise packaging and On-prem NVIDIA hosting.

Who makes Mistral-Large-2 (NIM)?

Mistral-Large-2 (NIM) is developed and served by Nvidia.