Mistral-Large-Instruct-2407: benchmark scores, price and ranking

Mistral-Large-Instruct-2407 from mistralai ranks #280 of 743 LLMs on the LLMs Tiger aggregate benchmark score (49.3), based on 1 benchmark results captured up to 2026-10-13.

Organisation: mistralai
Type: Open-weight / local model
Open weights: Yes
Aggregate rank: #280 of 743 (score 49.3)

Across the 1 benchmark where at least ten models are scored, Mistral-Large-Instruct-2407 is in the top 10% on 0 and in the top half on 1.

Mistral-Large-Instruct-2407 benchmark results

Mistral-Large-Instruct-2407 benchmark scores, ranked against all models measured on each benchmark
Benchmark	Score	Rank	Source	Captured
MMLU-Pro	65.9%	#48 of 136	HuggingFace MMLU-Pro leaderboard	2026-10-13

About Mistral-Large-Instruct-2407

Mistral-Large-Instruct-2407 is an open-weight model that can run on your own hardware from mistralai. No API price is listed for it yet. We hold 1 benchmark result for it across 1 area, and none is in the top tenth of its board.

Where Mistral-Large-Instruct-2407 stands

On our aggregate score, Mistral-Large-Instruct-2407 is #280 of 743 ranked models, around the middle of the table. Its score is 49.3; the scale is centred on 50, so it sits 0.7 points below the typical model. That beats 62% of the ranked field. Among the 10 ranked mistralai models it is #3. The next one up is Mistral-Large-Instruct-2411 at 49.6. The next one down is Mistral-Small-24B-Base-2501 at 47.7.

Mistral-Large-Instruct-2407, benchmark by benchmark

MMLU-Pro puts Mistral-Large-Instruct-2407 at 65.9%, #48 of 136. That beats 65% of the models tested, but 22.2 points short of Darwin-180B-RSI (88.1%). The results either side are Hunyuan-A13B-Instruct (67.3%) and DeepSeek-V2.5 (65.8%). It covers 57-subject knowledge + reasoning. The board median is 55.3%, so Mistral-Large-Instruct-2407 is 10.7 points above it. Source: HuggingFace MMLU-Pro leaderboard, captured 2026-10-13.

Reading these numbers

The 1 score on this page comes from 1 source: HuggingFace MMLU-Pro leaderboard (1). No official leaderboard supplied any of them, so treat them as third-party measurements. With 1 results the aggregate rank can move a lot when one new score arrives.

Models ranked nearby

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