Mistral Large 3 2512 vs Qwen2.5 72B Instruct
Mistral Large 3 2512 leads Qwen2.5 72B Instruct on the Artificial Analysis Intelligence Index, 9.3 to 7.7, and Qwen2.5 72B Instruct costs 3.8x less per output token ($0.40 vs $1.50 per million). Updated October 22, 2026; 3 benchmarks have a result for both.
Mistral Large 3 2512 or Qwen2.5 72B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Large 3 2512 for a larger context window (262K against 33K tokens).
- Shared results
- 3
- Mistral Large 3 2512 only
- 25
- Qwen2.5 72B Instruct only
- 50
- Like-for-like categories
- 2 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Mistral Large 3 2512
Mistral Large 3 2512 leads, 9.3 against 7.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Large 3 2512 has a AA Agentic Index result, 1.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Mistral Large 3 2512 has a GPQA Diamond result, 68.4%.
Directional only
Math
AIME
No call
Only Mistral Large 3 2512 has a AIME result, 42.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large 3 2512 has a MMLU Pro result, 79.8%.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Large 3 2512 has a Design Arena: websites result, 1162.
Directional only
Long documents
Listed context window
Mistral Large 3 2512
Mistral Large 3 2512 takes 262K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 72B Instruct
Mistral Large 3 2512 $0.0013, Qwen2.5 72B Instruct $0.0006 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Mistral Large 3 2512 has the number, $0.77.
Directional only
At a glance
- Coding index
- Mistral Large 3 2512 not benchmarked, Qwen2.5 72B Instruct not benchmarked.
- Widest category
- General, 2.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMCA: Mistral Large 3 2512 16.7% against Qwen2.5 72B Instruct 13.4%, 3.3 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 3 2512 $1.50 against Qwen2.5 72B Instruct $0.40 per million output tokens, 3.8x apart.
- Context window
- Mistral Large 3 2512 takes 262K tokens, Qwen2.5 72B Instruct 33K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Mistral Large 3 2512 | Bars | Qwen2.5 72B Instruct | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 3 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| AA Coding Index | 20.1 | Not measured | Only Mistral Large 3 2512 measured |
| LiveCodeBench (Vals AI) | 55.3% | Not measured | Only Mistral Large 3 2512 measured |
| SWE-bench Verified (Vals AI) | 41.4% | Not measured | Only Mistral Large 3 2512 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 27.6% | Only Qwen2.5 72B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 4.5% | Only Qwen2.5 72B Instruct measured |
| WeirdML | Not measured | 16.0% | Only Qwen2.5 72B Instruct measured |
| ALE-Bench | 264.7 | Not measured | Only Mistral Large 3 2512 measured |
| LMArena Text: coding | Not measured | 1292 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: software and IT | Not measured | 1292 | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large 3 2512 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.3 | 7.7 | Mistral Large 3 2512 |
| Epoch Capabilities Index | Not measured | 129.0 | Only Qwen2.5 72B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Mistral Large 3 2512 measured |
| τ²-Bench Telecom | Not measured | 34.5% | Only Qwen2.5 72B Instruct measured |
| METR time horizons | Not measured | 35.8% | Only Qwen2.5 72B Instruct measured |
| BALROG | Not measured | 16.2% | Only Qwen2.5 72B Instruct measured |
| TheAgentCompany | Not measured | 5.7% | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 68.4% | Not measured | Only Mistral Large 3 2512 measured |
| MMMU Pro (Vals AI) | 66.2% | Not measured | Only Mistral Large 3 2512 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 49.1% | Only Qwen2.5 72B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 3.6% | Only Qwen2.5 72B Instruct measured |
| GPQA Diamond (Epoch AI run) | Not measured | 49.1% | Only Qwen2.5 72B Instruct measured |
| BIG-Bench Hard | Not measured | 79.8% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts | Not measured | 1271 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: expert | Not measured | 1245 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts in English | Not measured | 1279 | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| AIME | 42.9% | Not measured | Only Mistral Large 3 2512 measured |
| MGSM (Vals AI) | 85.4% | Not measured | Only Mistral Large 3 2512 measured |
| AA Math Index | Not measured | 14.0 | Only Qwen2.5 72B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 14.0% | Only Qwen2.5 72B Instruct measured |
| OTIS Mock AIME | Not measured | 8.1% | Only Qwen2.5 72B Instruct measured |
| MATH level 5 | Not measured | 63.2% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: math | Not measured | 1283 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: mathematical work | Not measured | 1290 | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| MMLU Pro | 79.8% | Not measured | Only Mistral Large 3 2512 measured |
| LegalBench (Vals AI) | 79.1% | Not measured | Only Mistral Large 3 2512 measured |
| CaseLaw (Vals AI) | 61.4% | Not measured | Only Mistral Large 3 2512 measured |
| CorpFin (Vals AI) | 61.0% | Not measured | Only Mistral Large 3 2512 measured |
| TaxEval (Vals AI) | 73.1% | Not measured | Only Mistral Large 3 2512 measured |
| MortgageTax (Vals AI) | 52.1% | Not measured | Only Mistral Large 3 2512 measured |
| MedQA (Vals AI) | 82.2% | Not measured | Only Mistral Large 3 2512 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 72.0% | Only Qwen2.5 72B Instruct measured |
| MMLU | Not measured | 85.3% | Only Qwen2.5 72B Instruct measured |
| AI2 Reasoning Challenge | Not measured | 94.5% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: science | Not measured | 1275 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: medicine and healthcare | Not measured | 1258 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: legal and government | Not measured | 1288 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: business and finance | Not measured | 1253 | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: UI components | 1099 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: game dev | 1080 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: data viz | 1136 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: 3D | 1099 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: all code categories | 1141 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: SVG | 992 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: ASCII art | 1069 | Not measured | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mistral Large 3 2512 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 24.6% | Not measured | Only Mistral Large 3 2512 measured |
| IFBench | Not measured | 36.9% | Only Qwen2.5 72B Instruct measured |
| DTBench | 65.1% | 62.9% | Mistral Large 3 2512 |
| LMCA | 16.7% | 13.4% | Mistral Large 3 2512 |
| HellaSwag | Not measured | 84.8% | Only Qwen2.5 72B Instruct measured |
| WinoGrande | Not measured | 82.3% | Only Qwen2.5 72B Instruct measured |
| PIQA | Not measured | 82.6% | Only Qwen2.5 72B Instruct measured |
| LMArena Text | Not measured | 1269 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: instruction following | Not measured | 1254 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: creative writing | Not measured | 1221 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: English | Not measured | 1283 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: non-English | Not measured | 1252 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Chinese | Not measured | 1273 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: German | Not measured | 1234 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Japanese | Not measured | 1180 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Korean | Not measured | 1188 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: French | Not measured | 1280 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Spanish | Not measured | 1255 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Russian | Not measured | 1264 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: multi-turn | Not measured | 1272 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: longer queries | Not measured | 1281 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: writing and language | Not measured | 1247 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: entertainment and media | Not measured | 1211 | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 3 2512 | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen2.5 72B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 72B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 72B Instruct costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Mistral Large 3 2512 | Qwen2.5 72B Instruct |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | December 1, 2025 | September 19, 2024 |
| Context window | 262K | 33K |
| Input $/Mtok | $0.50 | $0.36 |
| Output $/Mtok | $1.50 | $0.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $0.77 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 3 2512 better than Qwen2.5 72B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Large 3 2512 for a larger context window (262K against 33K tokens).
Which is cheaper, Mistral Large 3 2512 or Qwen2.5 72B Instruct?
Mistral Large 3 2512 costs $0.50 per million input tokens and $1.50 per million output tokens; Qwen2.5 72B Instruct costs $0.36 and $0.40. Cost per solved task is known for Mistral Large 3 2512 only.
Which has the bigger context window, Mistral Large 3 2512 or Qwen2.5 72B Instruct?
Mistral Large 3 2512, with 262K tokens against 33K.
How many benchmarks is the Mistral Large 3 2512 vs Qwen2.5 72B Instruct comparison based on?
3 benchmarks have a result for both models as of October 22, 2026. Mistral Large 3 2512's coding index rests on 1 independent benchmark and Qwen2.5 72B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.