Mistral Large 3 Instruct on TruthfulQA: score, rank and what it means
Mistral Large 3 Instruct scores 85.5 on TruthfulQA, placing it #60 of 600 models in the index. The benchmark average is 73.6 and the leader is GPT-5.1 Max at 91.1.
Score distribution
The chart shows the top 10 models on TruthfulQA, with Mistral Large 3 Instruct highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 2 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 3 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 4 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 5 | GPT-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 6 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
| 7 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 8 | Qwen3-Max Max | Alibaba Cloud | 400000 | $18.53 | 85.9 |
| 9 | GPT-5.1 | OpenAI | 2000000 | $19.01 | 86.0 |
| 10 | GPT-5.1 Turbo | OpenAI | 2000000 | $19.19 | 86.1 |
What this score means
On TruthfulQA, Mistral Large 3 Instruct sits at #60 of 600. The leader, GPT-5.1 Max, scores 91.1, so the gap to the top is 5.6 points. The median model in this index scores 76.3, which puts Mistral Large 3 Instruct above the midpoint.
Mistral AI models average 71.0 on this benchmark. Mistral Large 3 Instruct is 14.5 points above that provider line, so it is a stronger result than the average Mistral AI model.
Among multimodal models, the average is 80.1. Mistral Large 3 Instruct is 5.4 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 85.5 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.
Price context
At $5.31 per million input tokens, Mistral Large 3 Instruct is above the median input price of $4.00 across the 600 models scored on TruthfulQA. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Claude Opus 4.5 Turbo | Anthropic | 2000000 | $19.57 | 85.7 |
| Gemini 2.5 Pro Max | Google DeepMind | 200000 | $16.94 | 84.8 |
| Gemini 2.5 Pro Pro | Google DeepMind | 400000 | $17.16 | 83.6 |
| Gemini 3 Flash Vision | Google DeepMind | 400000 | $15.06 | 81.9 |
| Mistral Large 3 Instruct | Mistral AI | 400000 | $5.31 | 81.1 |
| GPT-4.1 Max | OpenAI | 400000 | $17.34 | 84.7 |
| Grok 3 | xAI | 128000 | $15.84 | 82.8 |
Other benchmarks for Mistral Large 3 Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 82.3 | 116 | 81th | |
| GPQA Diamond | 79.8 | 60 | 90th | |
| SWE-bench Verified | 71.9 | 76 | 87th | |
| HumanEval | 84.2 | 129 | 79th | |
| MATH-500 | 83.4 | 140 | 77th | |
| AIME 2025 | 76.2 | 137 | 77th | |
| LiveCodeBench | 75.1 | 94 | 84th | |
| IFEval | 87.6 | 113 | 81th | |
| HellaSwag | 89.1 | 110 | 82th | |
| MMMU | 76.5 | 125 | 79th | |
| Arena Elo | 1446.2 | 88 | 85th |
FAQ
What score does Mistral Large 3 Instruct get on TruthfulQA?
Mistral Large 3 Instruct scores 85.5 on TruthfulQA in this index. The benchmark average is 73.6 and the top score is 91.1.
How does Mistral Large 3 Instruct rank on TruthfulQA?
It ranks #60 of 600 models, in the 90th percentile. The leader is GPT-5.1 Max at 91.1.
Is Mistral Large 3 Instruct good at TruthfulQA?
Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.
How is the TruthfulQA score calculated?
TruthfulQA is a safety benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.
What does Mistral Large 3 Instruct cost?
Mistral Large 3 Instruct costs $5.31 per million input tokens and $22.47 per million output tokens.