GPT-6 Astra vs Mistral Large
Updated October 21, 2026. 33 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 33 shared
Decision reading
Only GPT-6 Astra has a coding score, 85.1 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding.
Mistral Large has the edge where output tokens cost 8.3x less.
Model AGPT-6 AstraOpenAI85.1/1005 independent benchmarksNo cost per solved taskModel BMistral LargeMistral AINot benchmarkedNo coding benchmarkNo cost per solved task
- Shared results
- 33
- GPT-6 Astra only
- 86
- Mistral Large only
- 11
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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
Only GPT-6 Astra has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-6 Astra
GPT-6 Astra leads, 52.7 against 5.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-6 Astra has a AA Agentic Index result, 51.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Mistral Large has a GPQA Diamond result, 47.7%.
Directional only
Math
AIME
No call
Only Mistral Large has a AIME result, 9.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large has a MMLU Pro result, 69.7%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-6 Astra has a Design Arena: websites result, 1337.
Directional only
General
Vals Index
No call
Only GPT-6 Astra has a Vals Index result, 65.0%.
Directional only
Long documents
Listed context window
GPT-6 Astra
GPT-6 Astra takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large
GPT-6 Astra $0.035, Mistral Large $0.0050 per turn.
List prices
At a glance
- Coding index
- GPT-6 Astra 85.1 from 5 benchmarks, Mistral Large not benchmarked.
- Widest category
- Intelligence, 52.6 points apart on average over 2 shared benchmarks.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): GPT-6 Astra 96.3% against Mistral Large 35.1%, 61.2 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Astra $50.00 against Mistral Large $6.00 per million output tokens, 8.3x apart.
- Context window
- GPT-6 Astra takes 1.05M tokens, Mistral Large 128K.
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 | GPT-6 Astra | Bars | Mistral Large | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 33 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | GPT-6 Astra | Mistral Large | Leader |
|---|---|---|---|
| LiveBench coding | 93.7% | Not measured | Only GPT-6 Astra measured |
| LMArena WebDev | 1774 | Not measured | Only GPT-6 Astra measured |
| AA Coding Index | 76.9 | Not measured | Only GPT-6 Astra measured |
| LiveCodeBench (Vals AI) | Not measured | 37.1% | Only Mistral Large measured |
| Terminal-Bench 4 (Vals AI) | 59.6% | Not measured | Only GPT-6 Astra measured |
| Vibe Code Bench (Vals AI) | 89.6% | Not measured | Only GPT-6 Astra measured |
| Code migration (Vals AI) | 67.7% | Not measured | Only GPT-6 Astra measured |
| ProgramBench (Vals AI) | 5.5% | Not measured | Only GPT-6 Astra measured |
| IOI (Vals AI) | 100.0% | Not measured | Only GPT-6 Astra measured |
| Terminal-Bench 2.1 (Vals AI) | 87.3% | Not measured | Only GPT-6 Astra measured |
| SWE-bench Multimodal (Vals AI) | 43.3% | Not measured | Only GPT-6 Astra measured |
| Vibe Code Bench 1-100 (Vals AI) | 27.6% | Not measured | Only GPT-6 Astra measured |
| CyberBench (Vals AI) | 41.1% | Not measured | Only GPT-6 Astra measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 17.8% | Only Mistral Large measured |
| SciCode | 56.5% | Not measured | Only GPT-6 Astra measured |
| FrontierCode | 53.3% | Not measured | Only GPT-6 Astra measured |
| FrontierSWE | 65.5% | Not measured | Only GPT-6 Astra measured |
| GSO-Bench | 79.4% | Not measured | Only GPT-6 Astra measured |
| WeirdML | 93.3% | Not measured | Only GPT-6 Astra measured |
| MirrorCode | 46.7% | Not measured | Only GPT-6 Astra measured |
| ALE-Bench | 2951.3 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: coding | 1489 | 1275 | GPT-6 Astra |
| LMArena Text: software and IT | 1474 | 1274 | GPT-6 Astra |
| LMArena WebDev: React | 1798 | Not measured | Only GPT-6 Astra measured |
| LMArena WebDev: HTML | 1775 | Not measured | Only GPT-6 Astra measured |
| LMArena WebDev: from an image | 1726 | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 12 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6 Astra | Mistral Large | Leader |
|---|---|---|---|
| AA Intelligence Index | 52.7 | 5.8 | GPT-6 Astra |
| Epoch Capabilities Index | 168.8 | 122.1 | GPT-6 Astra |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index27 boards, none shared
| Benchmark | GPT-6 Astra | Mistral Large | Leader |
|---|---|---|---|
| AA Agentic Index | 51.0 | Not measured | Only GPT-6 Astra measured |
| Design Arena: agents building web apps | 1374 | Not measured | Only GPT-6 Astra measured |
| Design Arena: agents building full-stack apps | 1357 | Not measured | Only GPT-6 Astra measured |
| Design Arena: agents building mobile apps | 1312 | Not measured | Only GPT-6 Astra measured |
| Design Arena: agents building Godot games | 1348 | Not measured | Only GPT-6 Astra measured |
| Design Arena: PowerPoint slides | 1244 | Not measured | Only GPT-6 Astra measured |
| Design Arena: spreadsheets | 1369 | Not measured | Only GPT-6 Astra measured |
| LiveBench research | 85.2% | Not measured | Only GPT-6 Astra measured |
| LiveBench browser | 84.0% | Not measured | Only GPT-6 Astra measured |
| LiveBench long agentic | 82.4% | Not measured | Only GPT-6 Astra measured |
| SREBench (Vals AI) | 56.9% | Not measured | Only GPT-6 Astra measured |
| Finance Agent (Vals AI) | 53.5% | Not measured | Only GPT-6 Astra measured |
| Tax Agent Bench (Vals AI) | 20.7% | Not measured | Only GPT-6 Astra measured |
| Legal Research Bench (Vals AI) | 39.4% | Not measured | Only GPT-6 Astra measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 7.1% | Not measured | Only GPT-6 Astra measured |
| Excel Modeling Benchmark (Vals AI) | 71.7% | Not measured | Only GPT-6 Astra measured |
| BioMysteryBench (Vals AI) | 79.3% | Not measured | Only GPT-6 Astra measured |
| Terminal-Bench-Science (Vals AI) | 62.9% | Not measured | Only GPT-6 Astra measured |
| Vals Science Index | 65.1% | Not measured | Only GPT-6 Astra measured |
| Time Horizon Index (Vals AI) | 90.5% | Not measured | Only GPT-6 Astra measured |
| CUA-bench (Vals AI) | 19.2% | Not measured | Only GPT-6 Astra measured |
| Robo-bench (Vals AI) | 23.3% | Not measured | Only GPT-6 Astra measured |
| APEX-Agents | 64.7% | Not measured | Only GPT-6 Astra measured |
| Remote Labor Index | 20.8% | Not measured | Only GPT-6 Astra measured |
| BALROG | 68.3% | Not measured | Only GPT-6 Astra measured |
| SpireClimb | 25.7% | Not measured | Only GPT-6 Astra measured |
| Vending-Bench 2 | $15,515 | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 12 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-6 Astra | Mistral Large | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 47.7% | Only Mistral Large measured |
| LiveBench reasoning | 92.7% | Not measured | Only GPT-6 Astra measured |
| MysteryMechanism (Vals AI) | 53.1% | Not measured | Only GPT-6 Astra measured |
| GPQA Diamond (Artificial Analysis run) | 96.3% | 35.1% | GPT-6 Astra |
| Humanity's Last Exam (Artificial Analysis run) | 54.7% | 3.5% | GPT-6 Astra |
| GPQA Diamond (Epoch AI run) | 95.8% | Not measured | Only GPT-6 Astra measured |
| ARC-AGI | 98.5% | Not measured | Only GPT-6 Astra measured |
| ARC-AGI-2 | 95.0% | Not measured | Only GPT-6 Astra measured |
| Chess puzzles | 74.0% | Not measured | Only GPT-6 Astra measured |
| Mystery game puzzles | 84.0% | Not measured | Only GPT-6 Astra measured |
| EBR-bench | 76.2% | Not measured | Only GPT-6 Astra measured |
| LMArena Text: hard prompts | 1463 | 1257 | GPT-6 Astra |
| LMArena Text: expert | 1489 | 1208 | GPT-6 Astra |
| LMArena Text: hard prompts in English | 1464 | 1268 | GPT-6 Astra |
| LMArena Vision: diagrams | 1297 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision: homework | 1337 | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6 Astra | Mistral Large | Leader |
|---|---|---|---|
| AIME | Not measured | 9.2% | Only Mistral Large measured |
| MATH 500 (Vals AI) | Not measured | 74.4% | Only Mistral Large measured |
| MGSM (Vals AI) | Not measured | 87.2% | Only Mistral Large measured |
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6 Astra measured |
| FrontierMath, tiers 1 to 3 | 93.7% | Not measured | Only GPT-6 Astra measured |
| FrontierMath, tier 4 | 97.6% | Not measured | Only GPT-6 Astra measured |
| ProofBench | 99.0% | Not measured | Only GPT-6 Astra measured |
| LMArena Text: math | 1465 | 1261 | GPT-6 Astra |
| LMArena Text: mathematical work | 1484 | 1257 | GPT-6 Astra |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-6 Astra | Mistral Large | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 69.7% | Only Mistral Large measured |
| TaxEval (Vals AI) | Not measured | 63.8% | Only Mistral Large measured |
| MedQA (Vals AI) | Not measured | 76.2% | Only Mistral Large measured |
| MedCode (Vals AI) | 48.5% | Not measured | Only GPT-6 Astra measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 51.5% | Only Mistral Large measured |
| SimpleQA Verified | 75.6% | Not measured | Only GPT-6 Astra measured |
| MMLU | Not measured | 68.8% | Only Mistral Large measured |
| LMArena Text: science | 1451 | 1260 | GPT-6 Astra |
| LMArena Text: medicine and healthcare | 1425 | 1255 | GPT-6 Astra |
| LMArena Text: legal and government | 1462 | 1275 | GPT-6 Astra |
| LMArena Text: business and finance | 1439 | 1238 | GPT-6 Astra |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-6 Astra | Mistral Large | Leader |
|---|---|---|---|
| Design Arena: websites | 1337 | Not measured | Only GPT-6 Astra measured |
| Design Arena: UI components | 1396 | Not measured | Only GPT-6 Astra measured |
| Design Arena: game dev | 1476 | Not measured | Only GPT-6 Astra measured |
| Design Arena: data viz | 1334 | Not measured | Only GPT-6 Astra measured |
| Design Arena: 3D | 1500 | Not measured | Only GPT-6 Astra measured |
| Design Arena: all code categories | 1379 | Not measured | Only GPT-6 Astra measured |
| Design Arena: SVG | 1431 | Not measured | Only GPT-6 Astra measured |
| Design Arena: ASCII art | 1359 | Not measured | Only GPT-6 Astra measured |
| LiveBench design | 82.0% | Not measured | Only GPT-6 Astra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | GPT-6 Astra | Mistral Large | Leader |
|---|---|---|---|
| Vals Index | 65.0% | Not measured | Only GPT-6 Astra measured |
| LiveBench data analysis | 83.0% | Not measured | Only GPT-6 Astra measured |
| SAGE (Vals AI) | 46.4% | Not measured | Only GPT-6 Astra measured |
| MedScribe (Vals AI) | 87.9% | Not measured | Only GPT-6 Astra measured |
| Long context reasoning (AA-LCR) | 80.7% | Not measured | Only GPT-6 Astra measured |
| DTBench | 97.3% | 60.8% | GPT-6 Astra |
| LMCA | 64.4% | Not measured | Only GPT-6 Astra measured |
| Furniture assembly | 80.0% | Not measured | Only GPT-6 Astra measured |
| LMArena Text | 1441 | 1265 | GPT-6 Astra |
| LMArena Text: instruction following | 1455 | 1249 | GPT-6 Astra |
| LMArena Text: creative writing | 1420 | 1242 | GPT-6 Astra |
| LMArena Vision | 1280 | Not measured | Only GPT-6 Astra measured |
| LMArena Text: English | 1447 | 1284 | GPT-6 Astra |
| LMArena Text: non-English | 1432 | 1235 | GPT-6 Astra |
| LMArena Text: Chinese | 1489 | 1239 | GPT-6 Astra |
| LMArena Text: German | 1459 | 1242 | GPT-6 Astra |
| LMArena Text: Japanese | 1405 | 1170 | GPT-6 Astra |
| LMArena Text: Korean | 1428 | 1202 | GPT-6 Astra |
| LMArena Text: French | 1432 | 1325 | GPT-6 Astra |
| LMArena Text: Spanish | 1422 | 1268 | GPT-6 Astra |
| LMArena Text: Russian | 1438 | 1252 | GPT-6 Astra |
| LMArena Text: Polish | 1422 | 1157 | GPT-6 Astra |
| LMArena Text: multi-turn | 1447 | 1260 | GPT-6 Astra |
| LMArena Text: longer queries | 1460 | 1261 | GPT-6 Astra |
| LMArena Text: writing and language | 1437 | 1261 | GPT-6 Astra |
| LMArena Text: entertainment and media | 1427 | 1230 | GPT-6 Astra |
| LMArena Vision: English | 1280 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision: Chinese | 1361 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision: reading text | 1292 | Not measured | Only GPT-6 Astra measured |
| LMArena Vision: creative writing | 1286 | Not measured | Only GPT-6 Astra measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6 Astra | Mistral Large | 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
GPT-6 Astra$0.035Fits in one request
Mistral Large$0.0050Fits in one request
Mistral Large costs less
Repository review
50K input + 3K output tokens
GPT-6 Astra$0.650Fits in one request
Mistral Large$0.118Fits in one request
Mistral Large costs less
Agent loop
200K input + 10K output tokens
GPT-6 Astra$2.50Fits in one request
Mistral Large$0.460Exceeds the context window
Mistral Large 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 | OpenAI GPT-6 Astra | Mistral Large |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | September 4, 2026 | February 26, 2024 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $10.00 | $2.00 |
| Output $/Mtok | $50.00 | $6.00 |
| Coding index | 85.1 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Astra better than Mistral Large for coding?
Only GPT-6 Astra has a coding score, 85.1 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding. Mistral Large has the edge where output tokens cost 8.3x less.
Which is cheaper, GPT-6 Astra or Mistral Large?
GPT-6 Astra costs $10.00 per million input tokens and $50.00 per million output tokens; Mistral Large costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6 Astra or Mistral Large?
GPT-6 Astra, with 1.05M tokens against 128K.
How many benchmarks is the GPT-6 Astra vs Mistral Large comparison based on?
33 benchmarks have a result for both models as of October 21, 2026. GPT-6 Astra's coding index rests on 5 independent benchmarks and Mistral Large's on 0. Where only one model has a result, the page says so instead of naming a winner.