GPT-6.1 Terra vs Mistral Medium 3.5
GPT-6.1 Terra leads Mistral Medium 3.5 on coding, 77.4 to 25.4 on the Vibe Coding Index, and GPT-6.1 Terra costs 1.5x less per output token ($5.00 vs $7.50 per million). Updated October 29, 2026; 14 benchmarks have a result for both.
GPT-6.1 Terra or Mistral Medium 3.5: which to pick
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 25.4 for Mistral Medium 3.5.
Mistral Medium 3.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 14
- GPT-6.1 Terra only
- 22
- Mistral Medium 3.5 only
- 67
- Like-for-like categories
- 5 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
GPT-6.1 Terra
GPT-6.1 Terra scores 77.4 against 25.4.
4 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-6.1 Terra has a AA Intelligence Index result, 51.0.
Directional only
Agentic work
AA Agentic Index
No call
Only Mistral Medium 3.5 has a AA Agentic Index result, 7.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Mistral Medium 3.5 has a GPQA Diamond result, 34.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Medium 3.5 has a MMLU Pro result, 75.3%.
Directional only
Web design
Design Arena: websites
GPT-6.1 Terra
GPT-6.1 Terra leads, 1283 against 1141.
Same board, both measured
General
Vals Index
No call
Only GPT-6.1 Terra has a Vals Index result, 60.5%.
Directional only
Long documents
Listed context window
GPT-6.1 Terra
GPT-6.1 Terra takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6.1 Terra
GPT-6.1 Terra $0.0035, Mistral Medium 3.5 $0.0053 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Mistral Medium 3.5 has the number, $6.02.
Directional only
At a glance
- Coding index
- GPT-6.1 Terra 77.4 from 4 benchmarks, Mistral Medium 3.5 25.4 from 3 benchmarks.
- Widest category
- Coding, 53.7 points apart on average over 6 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-6.1 Terra 84.0% against Mistral Medium 3.5 2.9%, 81.1 points apart on a 0 to 100 scale.
- Output price
- GPT-6.1 Terra $5.00 against Mistral Medium 3.5 $7.50 per million output tokens, 1.5x apart.
- Context window
- GPT-6.1 Terra takes 1.05M tokens, Mistral Medium 3.5 262K.
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-6.1 Terra | Bars | Mistral Medium 3.5 | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 1 | 0 | ||
| Web design | 4 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 14 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
| Benchmark | GPT-6.1 Terra | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| LiveBench coding | 94.3% | Not measured | Only GPT-6.1 Terra measured |
| LMArena WebDev | 1673 | 1264 | GPT-6.1 Terra |
| AA Coding Index | Not measured | 46.9 | Only Mistral Medium 3.5 measured |
| SWE-bench Verified (Vals AI) | Not measured | 66.4% | Only Mistral Medium 3.5 measured |
| Terminal-Bench 4 (Vals AI) | 49.5% | Not measured | Only GPT-6.1 Terra measured |
| Vibe Code Bench (Vals AI) | 84.0% | 2.9% | GPT-6.1 Terra |
| Code migration (Vals AI) | Not measured | 5.1% | Only Mistral Medium 3.5 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 39.0% | Only Mistral Medium 3.5 measured |
| SciCode | 55.1% | 40.2% | GPT-6.1 Terra |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 33.3% | Only Mistral Medium 3.5 measured |
| ALE-Bench | 2608.8 | 764.0 | GPT-6.1 Terra |
| LMArena Text: coding | Not measured | 1460 | Only Mistral Medium 3.5 measured |
| LMArena Text: software and IT | Not measured | 1458 | Only Mistral Medium 3.5 measured |
| LMArena WebDev: React | 1657 | 1254 | GPT-6.1 Terra |
| LMArena WebDev: HTML | 1719 | 1308 | GPT-6.1 Terra |
| Neither model has a result on the other 28 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-6.1 Terra | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 51.0 | Not measured | Only GPT-6.1 Terra measured |
| Epoch Capabilities Index | Not measured | 141.4 | Only Mistral Medium 3.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6.1 Terra | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 7.0 | Only Mistral Medium 3.5 measured |
| LiveBench research | 73.9% | Not measured | Only GPT-6.1 Terra measured |
| LiveBench browser | 93.1% | Not measured | Only GPT-6.1 Terra measured |
| LiveBench long agentic | 48.6% | Not measured | Only GPT-6.1 Terra measured |
| Finance Agent (Vals AI) | Not measured | 32.1% | Only Mistral Medium 3.5 measured |
| Tax Agent Bench (Vals AI) | 15.2% | 4.5% | GPT-6.1 Terra |
| Legal Research Bench (Vals AI) | 26.0% | 9.1% | GPT-6.1 Terra |
| Harvey's Legal Agent Benchmark (Vals AI) | 1.7% | Not measured | Only GPT-6.1 Terra measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 11.2% | Only Mistral Medium 3.5 measured |
| τ²-Bench Telecom | Not measured | 94.2% | Only Mistral Medium 3.5 measured |
| APEX-Agents | 68.3% | Not measured | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Terra | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 34.9% | Only Mistral Medium 3.5 measured |
| LiveBench reasoning | 88.7% | Not measured | Only GPT-6.1 Terra measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 74.8% | Only Mistral Medium 3.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 46.2% | 13.8% | GPT-6.1 Terra |
| GPQA Diamond (Epoch AI run) | 94.3% | Not measured | Only GPT-6.1 Terra measured |
| Mystery game puzzles | 74.0% | Not measured | Only GPT-6.1 Terra measured |
| EBR-bench | 78.1% | Not measured | Only GPT-6.1 Terra measured |
| LMArena Text: hard prompts | Not measured | 1437 | Only Mistral Medium 3.5 measured |
| LMArena Text: expert | Not measured | 1432 | Only Mistral Medium 3.5 measured |
| LMArena Text: hard prompts in English | Not measured | 1445 | Only Mistral Medium 3.5 measured |
| LMArena Vision: diagrams | Not measured | 1254 | Only Mistral Medium 3.5 measured |
| LMArena Vision: homework | Not measured | 1230 | Only Mistral Medium 3.5 measured |
| Kagi LLM Benchmark | Not measured | 41.4% | Only Mistral Medium 3.5 measured |
| Humanity's Last Exam (Scale run) | 35.7% | Not measured | Only GPT-6.1 Terra measured |
| Neither model has a result on the other 9 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-6.1 Terra | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6.1 Terra measured |
| FrontierMath, tiers 1 to 3 | 90.9% | Not measured | Only GPT-6.1 Terra measured |
| FrontierMath, tier 4 | 92.7% | Not measured | Only GPT-6.1 Terra measured |
| ProofBench | Not measured | 9.0% | Only Mistral Medium 3.5 measured |
| LMArena Text: math | Not measured | 1432 | Only Mistral Medium 3.5 measured |
| LMArena Text: mathematical work | Not measured | 1441 | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | GPT-6.1 Terra | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 75.3% | Only Mistral Medium 3.5 measured |
| CaseLaw (Vals AI) | Not measured | 44.2% | Only Mistral Medium 3.5 measured |
| CorpFin (Vals AI) | Not measured | 58.8% | Only Mistral Medium 3.5 measured |
| TaxEval (Vals AI) | Not measured | 68.0% | Only Mistral Medium 3.5 measured |
| MortgageTax (Vals AI) | Not measured | 28.9% | Only Mistral Medium 3.5 measured |
| MedCode (Vals AI) | Not measured | 33.8% | Only Mistral Medium 3.5 measured |
| SimpleQA Verified | 57.3% | Not measured | Only GPT-6.1 Terra measured |
| LMArena Text: science | Not measured | 1428 | Only Mistral Medium 3.5 measured |
| LMArena Text: medicine and healthcare | Not measured | 1409 | Only Mistral Medium 3.5 measured |
| LMArena Text: legal and government | Not measured | 1437 | Only Mistral Medium 3.5 measured |
| LMArena Text: business and finance | Not measured | 1426 | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 9 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-6.1 Terra | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1283 | 1141 | GPT-6.1 Terra |
| Design Arena: UI components | 1277 | 1074 | GPT-6.1 Terra |
| Design Arena: game dev | 1348 | 1078 | GPT-6.1 Terra |
| Design Arena: data viz | Not measured | 1121 | Only Mistral Medium 3.5 measured |
| Design Arena: 3D | Not measured | 1057 | Only Mistral Medium 3.5 measured |
| Design Arena: all code categories | 1295 | 1120 | GPT-6.1 Terra |
| Design Arena: SVG | Not measured | 947 | Only Mistral Medium 3.5 measured |
| Design Arena: ASCII art | Not measured | 1060 | Only Mistral Medium 3.5 measured |
| LiveBench design | 82.3% | Not measured | Only GPT-6.1 Terra measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Terra | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| Vals Index | 60.5% | Not measured | Only GPT-6.1 Terra measured |
| LiveBench data analysis | 82.3% | Not measured | Only GPT-6.1 Terra measured |
| SAGE (Vals AI) | Not measured | 72.0% | Only Mistral Medium 3.5 measured |
| MedScribe (Vals AI) | Not measured | 67.7% | Only Mistral Medium 3.5 measured |
| Vals Multimodal Index | Not measured | 34.8% | Only Mistral Medium 3.5 measured |
| IFBench | Not measured | 68.8% | Only Mistral Medium 3.5 measured |
| Long context reasoning (AA-LCR) | 82.7% | 69.3% | GPT-6.1 Terra |
| DTBench | Not measured | 75.5% | Only Mistral Medium 3.5 measured |
| LMCA | Not measured | 26.1% | Only Mistral Medium 3.5 measured |
| Surface Evolver Bench | Not measured | 26.9% | Only Mistral Medium 3.5 measured |
| Furniture assembly | 79.2% | Not measured | Only GPT-6.1 Terra measured |
| LMArena Text | Not measured | 1421 | Only Mistral Medium 3.5 measured |
| LMArena Text: instruction following | Not measured | 1415 | Only Mistral Medium 3.5 measured |
| LMArena Text: creative writing | Not measured | 1374 | Only Mistral Medium 3.5 measured |
| LMArena Vision | Not measured | 1222 | Only Mistral Medium 3.5 measured |
| LMArena Text: English | Not measured | 1433 | Only Mistral Medium 3.5 measured |
| LMArena Text: non-English | Not measured | 1405 | Only Mistral Medium 3.5 measured |
| LMArena Text: Chinese | Not measured | 1445 | Only Mistral Medium 3.5 measured |
| LMArena Text: German | Not measured | 1453 | Only Mistral Medium 3.5 measured |
| LMArena Text: Korean | Not measured | 1384 | Only Mistral Medium 3.5 measured |
| LMArena Text: French | Not measured | 1449 | Only Mistral Medium 3.5 measured |
| LMArena Text: Spanish | Not measured | 1411 | Only Mistral Medium 3.5 measured |
| LMArena Text: Russian | Not measured | 1396 | Only Mistral Medium 3.5 measured |
| LMArena Text: Polish | Not measured | 1430 | Only Mistral Medium 3.5 measured |
| LMArena Text: multi-turn | Not measured | 1423 | Only Mistral Medium 3.5 measured |
| LMArena Text: longer queries | Not measured | 1415 | Only Mistral Medium 3.5 measured |
| LMArena Text: writing and language | Not measured | 1384 | Only Mistral Medium 3.5 measured |
| LMArena Text: entertainment and media | Not measured | 1382 | Only Mistral Medium 3.5 measured |
| LMArena Vision: English | Not measured | 1240 | Only Mistral Medium 3.5 measured |
| LMArena Vision: Chinese | Not measured | 1244 | Only Mistral Medium 3.5 measured |
| LMArena Vision: reading text | Not measured | 1233 | Only Mistral Medium 3.5 measured |
| LMArena Vision: humor | Not measured | 1216 | Only Mistral Medium 3.5 measured |
| LMArena Vision: creative writing | Not measured | 1198 | Only Mistral Medium 3.5 measured |
| MultiChallenge | 74.2% | Not measured | Only GPT-6.1 Terra measured |
| EQ-Bench 4 | Not measured | 983 | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6.1 Terra | Mistral Medium 3.5 | 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-6.1 Terra costs less
Repository review
50K input + 3K output tokens
GPT-6.1 Terra costs less
Agent loop
200K input + 10K output tokens
GPT-6.1 Terra 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-6.1 Terra | Mistral Medium 3.5 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | October 26, 2026 | April 30, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $1.00 | $1.50 |
| Output $/Mtok | $5.00 | $7.50 |
| Coding index | 77.4 | 25.4 |
| Independent measurements behind it | 4 | 3 |
| Cost per solved task | Not computable | $6.02 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6.1 Terra better than Mistral Medium 3.5 for coding?
Pick GPT-6.1 Terra for coding: it scores 77.4 on the Vibe Coding Index against 25.4 for Mistral Medium 3.5. Mistral Medium 3.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, GPT-6.1 Terra or Mistral Medium 3.5?
GPT-6.1 Terra costs $1.00 per million input tokens and $5.00 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Cost per solved task is known for Mistral Medium 3.5 only.
Which has the bigger context window, GPT-6.1 Terra or Mistral Medium 3.5?
GPT-6.1 Terra, with 1.05M tokens against 262K.
How many benchmarks is the GPT-6.1 Terra vs Mistral Medium 3.5 comparison based on?
14 benchmarks have a result for both models as of October 29, 2026. GPT-6.1 Terra's coding index rests on 4 independent benchmarks and Mistral Medium 3.5's on 3. Where only one model has a result, the page says so instead of naming a winner.