Model comparison
GPT-5.6 Terra vs Mistral Medium
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 36.3 on the Noometry Index. Mistral Medium costs 1.5× less per token, which makes it the better buy when GPT-5.6 Terra's lead doesn't matter for your workload.
Last verified . 30 shared benchmarks.
Mistral AISummary
- They share 30 benchmarks with published results for both. GPT-5.6 Terra scores higher in 10 categories and Mistral Medium in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Terra leads 81.6 to 28.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 99.7% for GPT-5.6 Terra and 32.2% for Mistral Medium.
- Mistral Medium is cheaper at $1.50 / $7.50 per million input/output tokens, against $2 / $12 for GPT-5.6 Terra.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 262K.
- Mistral Medium has downloadable open weights; the other is API-only.
Side by side
| GPT-5.6 Terra | Mistral Medium | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 59.2 | 36.3 |
| Released | 2026-07-09 | 2023-12-11 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 128K | 262K |
| Input $ / M tokens | $2 | $1.50 |
| Output $ / M tokens | $12 | $7.50 |
| Results tracked | 52 | 36 |
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Category by category
Coding GPT-5.6 Terra leads
GPT-5.6 Terra: 57.7 (#19), Mistral Medium: 34.2 (#243)
| Benchmark | GPT-5.6 Terra | Mistral Medium |
|---|---|---|
| FrontierCode | 41.3% | 8% |
| SciCode | 55% | 40.2% |
| WeirdML | 78.3% | 43.7% |
| LMArena Coding | 1484 | 1434 |
| ALE-Bench | 1,951 | 763.98 |
| DeepSWE | 69.6% | — |
| CursorBench | 41.3% | — |
| LMArena WebDev | 1522 | — |
Agentic & Tool Use GPT-5.6 Terra leads
GPT-5.6 Terra: 40.1 (#25), Mistral Medium: 28.3 (#90)
| Benchmark | GPT-5.6 Terra | Mistral Medium |
|---|---|---|
| APEX-Agents | 58.2% | — |
| Berkeley Function Calling Leaderboard | — | 37.7% |
| BALROG | 53.2% | — |
| GDP.pdf | 24.7% | — |
| Vending-Bench 2 | 7,343 | — |
Reasoning GPT-5.6 Terra leads
GPT-5.6 Terra: 60.7 (#21), Mistral Medium: 24.0 (#167)
| Benchmark | GPT-5.6 Terra | Mistral Medium |
|---|---|---|
| Kagi LLM Benchmark | 51.3% | 50% |
| CritPt | 30% | 0% |
| LMArena Hard Prompts | 1468 | 1426 |
| DTBench | 93.3% | 75.5% |
| LMCA | 55% | 26.1% |
| Surface Evolver Bench | 83.8% | 26.9% |
| ARC-AGI-2 | 83.9% | — |
| SimpleBench | 48.9% | — |
| NYT Connections (extended) | 78.4% | — |
| ARC-AGI-1 | 96.5% | — |
| Chess Puzzles | 54% | — |
| Mystery Game Puzzles | 35% | — |
| Epoch Capabilities Index | 159.62 | — |
Math GPT-5.6 Terra leads
GPT-5.6 Terra: 81.6 (#12), Mistral Medium: 28.1 (#245)
| Benchmark | GPT-5.6 Terra | Mistral Medium |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 99.7% | 32.2% |
| ProofBench | 74% | 9% |
| LMArena Math | 1466 | 1408 |
| FrontierMath (Tiers 1-3) | 86% | — |
| FrontierMath Tier 4 | 70.7% | — |
| MATH Level 5 | — | 81.6% |
| FrontierMath (Feb 2025 set) | — | 0.3% |
Knowledge GPT-5.6 Terra leads
GPT-5.6 Terra: 61.2 (#30), Mistral Medium: 25.0 (#265)
| Benchmark | GPT-5.6 Terra | Mistral Medium |
|---|---|---|
| GPQA Diamond | 93.3% | 59.5% |
| LMArena Expert | 1492 | 1408 |
| Humanity's Last Exam | — | 4.5% |
| SimpleQA Verified | 43.2% | — |
| Vectara Hallucination Rate | — | 22.7% |
Multimodal GPT-5.6 Terra leads
GPT-5.6 Terra: 47.3 (#11), Mistral Medium: 35.3 (#88)
| Benchmark | GPT-5.6 Terra | Mistral Medium |
|---|---|---|
| LMArena Vision | 1271 | 1172 |
| Blueprint-Bench 2 | 30.8% | — |
| Furniture Assembly | 54.2% | — |
| LMArena Document | 1472 | — |
Multilingual GPT-5.6 Terra leads
GPT-5.6 Terra: 54.4 (#44), Mistral Medium: 52.1 (#91)
| Benchmark | GPT-5.6 Terra | Mistral Medium |
|---|---|---|
| LMArena Non-English | 1439 | 1408 |
| LMArena Chinese | 1513 | 1447 |
| LMArena French | 1471 | 1459 |
| LMArena German | 1460 | 1432 |
| LMArena Japanese | 1457 | 1378 |
| LMArena Korean | 1425 | 1380 |
| LMArena Russian | 1450 | 1411 |
| LMArena Spanish | 1448 | 1433 |
Instruction Following GPT-5.6 Terra leads
GPT-5.6 Terra: 76.4 (#40), Mistral Medium: 73.7 (#116)
| Benchmark | GPT-5.6 Terra | Mistral Medium |
|---|---|---|
| LMArena Instruction Following | 1454 | 1398 |
Long Context GPT-5.6 Terra leads
GPT-5.6 Terra: 44.4 (#68), Mistral Medium: 42.9 (#114)
| Benchmark | GPT-5.6 Terra | Mistral Medium |
|---|---|---|
| LMArena Longer Query | 1451 | 1406 |
Writing & Preference GPT-5.6 Terra leads
GPT-5.6 Terra: 70.2 (#23), Mistral Medium: 60.0 (#103)
| Benchmark | GPT-5.6 Terra | Mistral Medium |
|---|---|---|
| LMArena Text | 1447 | 1424 |
| LMArena Creative Writing | 1410 | 1391 |
| LMArena Multi-Turn | 1449 | 1418 |
| Short-Story Creative Writing | — | 77.3% |
| EQ-Bench Creative Writing | 1855 | — |
| EQ-Bench 4 | 1234 | — |
Frequently asked questions
Is GPT-5.6 Terra better than Mistral Medium?
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 36.3 on the Noometry Index. Mistral Medium costs 1.5× less per token, which makes it the better buy when GPT-5.6 Terra's lead doesn't matter for your workload.
Which is cheaper, GPT-5.6 Terra or Mistral Medium?
Mistral Medium is cheaper. It lists at $1.50 per million input tokens and $7.50 per million output tokens; GPT-5.6 Terra lists at $2 and $12.
Is GPT-5.6 Terra or Mistral Medium better for coding?
GPT-5.6 Terra scores higher on coding benchmarks: 57.7 versus 34.2 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Terra does, with 1.05M tokens against 262K.
How many benchmarks do GPT-5.6 Terra and Mistral Medium share?
30 benchmarks have published results for both models. GPT-5.6 Terra has 52 scored results on Noometry and Mistral Medium has 36.