Gemini 3.7 Flash vs MiniMax M2.7
Updated October 21, 2026. 64 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Gemini 3.7 Flash for coding: it scores 69.9 on the Vibe Coding Index against 28.4 for MiniMax M2.7.
Pick MiniMax M2.7 when output tokens cost 3.1x less, or when a solved task costs $0.64 against $1.78.
- Shared results
- 64
- Gemini 3.7 Flash only
- 48
- MiniMax M2.7 only
- 10
- Like-for-like categories
- 8 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, four public coding benchmarks
Gemini 3.7 Flash
Gemini 3.7 Flash scores 69.9 against 28.4.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 39.6 against 22.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only MiniMax M2.7 has a AA Agentic Index result, 15.3.
Directional only
Reasoning
GPQA Diamond
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 93.9% against 86.6%.
Same board, both measured
Math
AIME
No call
Only MiniMax M2.7 has a AIME result, 91.0%.
Directional only
Knowledge
MMLU Pro
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 90.1% against 80.4%.
Same board, both measured
Web design
Design Arena: websites
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 1304 against 1243.
Same board, both measured
Long documents
Listed context window
Gemini 3.7 Flash
Gemini 3.7 Flash takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.7
Gemini 3.7 Flash $0.0026, MiniMax M2.7 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiniMax M2.7
Gemini 3.7 Flash $1.78, MiniMax M2.7 $0.64.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 3.7 Flash 69.9 from 2 benchmarks, MiniMax M2.7 28.4 from 1 benchmark.
- Widest category
- Agentic work, 28.5 points apart on average over 4 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Gemini 3.7 Flash 70.4% against MiniMax M2.7 11.9%, 58.5 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.7 Flash $3.75 against MiniMax M2.7 $1.20 per million output tokens, 3.1x apart.
- Context window
- Gemini 3.7 Flash takes 1.05M tokens, MiniMax M2.7 205K.
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 | Gemini 3.7 Flash | Bars | MiniMax M2.7 | Ties |
|---|---|---|---|---|
| Coding | 13 | 0 | 1 tie | |
| Intelligence | 2 | 0 | ||
| Agentic work | 4 | 0 | ||
| Reasoning | 6 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 8 | 0 | ||
| Web design | 8 | 0 | ||
| General | 19 | 0 | ||
| All shared boards | 63 | 0 | 1 tie |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index130
| Benchmark | Gemini 3.7 Flash | MiniMax M2.7 | Leader |
|---|---|---|---|
| LiveBench coding | 80.5% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena WebDev | 1591 | 1399 | Gemini 3.7 Flash |
| AA Coding Index | 71.5 | 52.6 | Gemini 3.7 Flash |
| LiveCodeBench (Vals AI) | 88.7% | 79.9% | Gemini 3.7 Flash |
| SWE-bench Verified (Vals AI) | 80.8% | 73.8% | Gemini 3.7 Flash |
| Terminal-Bench 4 (Vals AI) | 12.1% | Not measured | Only Gemini 3.7 Flash measured |
| Vibe Code Bench (Vals AI) | 70.4% | 11.9% | Gemini 3.7 Flash |
| Code migration (Vals AI) | 34.8% | 8.7% | Gemini 3.7 Flash |
| ProgramBench (Vals AI) | 0.0% | 0.0% | Tie |
| IOI (Vals AI) | 67.8% | Not measured | Only Gemini 3.7 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 77.5% | 48.7% | Gemini 3.7 Flash |
| SkillsBench (Vals AI) | 65.9% | Not measured | Only Gemini 3.7 Flash measured |
| CyberBench (Vals AI) | 43.8% | Not measured | Only Gemini 3.7 Flash measured |
| SciCode | 59.8% | 50.1% | Gemini 3.7 Flash |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 39.4% | Only MiniMax M2.7 measured |
| Terminal-Bench | Not measured | 45.1% | Only MiniMax M2.7 measured |
| FrontierCode | 43.6% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierSWE | 20.3% | Not measured | Only Gemini 3.7 Flash measured |
| WeirdML | Not measured | 37.0% | Only MiniMax M2.7 measured |
| ALE-Bench | 904.3 | 599.3 | Gemini 3.7 Flash |
| LMArena Text: coding | 1499 | 1454 | Gemini 3.7 Flash |
| LMArena Text: software and IT | 1498 | 1446 | Gemini 3.7 Flash |
| LMArena WebDev: React | 1587 | 1388 | Gemini 3.7 Flash |
| LMArena WebDev: HTML | 1593 | 1401 | Gemini 3.7 Flash |
| LMArena WebDev: from an image | 1599 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 3.7 Flash | MiniMax M2.7 | Leader |
|---|---|---|---|
| AA Intelligence Index | 39.6 | 22.8 | Gemini 3.7 Flash |
| Epoch Capabilities Index | 158.0 | 145.8 | Gemini 3.7 Flash |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 3.7 Flash | MiniMax M2.7 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 15.3 | Only MiniMax M2.7 measured |
| Design Arena: agents building web apps | 1224 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building full-stack apps | 1208 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building mobile apps | 1230 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Android apps | 1247 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Godot games | 1264 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building games | 1235 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: spreadsheets | 1028 | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench research | 76.5% | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench browser | 56.0% | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench long agentic | 28.3% | Not measured | Only Gemini 3.7 Flash measured |
| SREBench (Vals AI) | 4.6% | Not measured | Only Gemini 3.7 Flash measured |
| Finance Agent (Vals AI) | 59.0% | 27.9% | Gemini 3.7 Flash |
| Tax Agent Bench (Vals AI) | 22.8% | 6.9% | Gemini 3.7 Flash |
| Legal Research Bench (Vals AI) | 34.6% | 10.6% | Gemini 3.7 Flash |
| Excel Modeling Benchmark (Vals AI) | 71.3% | 28.4% | Gemini 3.7 Flash |
| Terminal-Bench-Science (Vals AI) | 7.1% | Not measured | Only Gemini 3.7 Flash measured |
| τ²-Bench Telecom | Not measured | 84.8% | Only MiniMax M2.7 measured |
| APEX-Agents | 67.8% | Not measured | Only Gemini 3.7 Flash measured |
| Remote Labor Index | 5.0% | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Gemini 3.7 Flash | MiniMax M2.7 | Leader |
|---|---|---|---|
| GPQA Diamond | 93.9% | 86.6% | Gemini 3.7 Flash |
| LiveBench reasoning | 87.8% | Not measured | Only Gemini 3.7 Flash measured |
| MMMU Pro (Vals AI) | 89.0% | Not measured | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 94.5% | 87.4% | Gemini 3.7 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 47.9% | 29.6% | Gemini 3.7 Flash |
| GPQA Diamond (Epoch AI run) | 94.8% | Not measured | Only Gemini 3.7 Flash measured |
| ARC-AGI | 95.5% | Not measured | Only Gemini 3.7 Flash measured |
| ARC-AGI-2 | 84.6% | Not measured | Only Gemini 3.7 Flash measured |
| Chess puzzles | 66.0% | Not measured | Only Gemini 3.7 Flash measured |
| Mystery game puzzles | 37.0% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts | 1495 | 1422 | Gemini 3.7 Flash |
| LMArena Text: expert | 1512 | 1443 | Gemini 3.7 Flash |
| LMArena Text: hard prompts in English | 1487 | 1441 | Gemini 3.7 Flash |
| LMArena Vision: diagrams | 1329 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: homework | 1320 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemini 3.7 Flash | MiniMax M2.7 | Leader |
|---|---|---|---|
| AIME | Not measured | 91.0% | Only MiniMax M2.7 measured |
| OTIS Mock AIME | 97.2% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierMath, tiers 1 to 3 | 71.6% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierMath, tier 4 | 36.6% | Not measured | Only Gemini 3.7 Flash measured |
| ProofBench | 58.0% | 3.0% | Gemini 3.7 Flash |
| LMArena Text: math | 1511 | 1421 | Gemini 3.7 Flash |
| LMArena Text: mathematical work | 1502 | 1437 | Gemini 3.7 Flash |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Gemini 3.7 Flash | MiniMax M2.7 | Leader |
|---|---|---|---|
| MMLU Pro | 90.1% | 80.4% | Gemini 3.7 Flash |
| LegalBench (Vals AI) | 87.3% | 84.0% | Gemini 3.7 Flash |
| CaseLaw (Vals AI) | Not measured | 60.9% | Only MiniMax M2.7 measured |
| CorpFin (Vals AI) | Not measured | 61.2% | Only MiniMax M2.7 measured |
| TaxEval (Vals AI) | 74.7% | 66.6% | Gemini 3.7 Flash |
| MortgageTax (Vals AI) | 66.7% | Not measured | Only Gemini 3.7 Flash measured |
| MedCode (Vals AI) | 53.4% | 34.4% | Gemini 3.7 Flash |
| SimpleQA Verified | 69.2% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: science | 1511 | 1416 | Gemini 3.7 Flash |
| LMArena Text: medicine and healthcare | 1494 | 1409 | Gemini 3.7 Flash |
| LMArena Text: legal and government | 1496 | 1403 | Gemini 3.7 Flash |
| LMArena Text: business and finance | 1479 | 1407 | Gemini 3.7 Flash |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Gemini 3.7 Flash | MiniMax M2.7 | Leader |
|---|---|---|---|
| Design Arena: websites | 1304 | 1243 | Gemini 3.7 Flash |
| Design Arena: UI components | 1299 | 1210 | Gemini 3.7 Flash |
| Design Arena: game dev | 1318 | 1210 | Gemini 3.7 Flash |
| Design Arena: data viz | 1315 | 1233 | Gemini 3.7 Flash |
| Design Arena: 3D | 1308 | 1195 | Gemini 3.7 Flash |
| Design Arena: all code categories | 1308 | 1233 | Gemini 3.7 Flash |
| Design Arena: SVG | 1283 | 1136 | Gemini 3.7 Flash |
| Design Arena: ASCII art | 1276 | 1136 | Gemini 3.7 Flash |
| LiveBench design | 73.2% | Not measured | Only Gemini 3.7 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
| Benchmark | Gemini 3.7 Flash | MiniMax M2.7 | Leader |
|---|---|---|---|
| LiveBench data analysis | 68.0% | Not measured | Only Gemini 3.7 Flash measured |
| SAGE (Vals AI) | 49.2% | Not measured | Only Gemini 3.7 Flash measured |
| MedScribe (Vals AI) | 83.9% | 79.9% | Gemini 3.7 Flash |
| IFBench | Not measured | 75.7% | Only MiniMax M2.7 measured |
| Long context reasoning (AA-LCR) | 83.0% | 78.3% | Gemini 3.7 Flash |
| DTBench | 96.8% | Not measured | Only Gemini 3.7 Flash measured |
| LMCA | 50.4% | Not measured | Only Gemini 3.7 Flash measured |
| Furniture assembly | 26.7% | Not measured | Only Gemini 3.7 Flash measured |
| ExploitBench | Not measured | 13.3% | Only MiniMax M2.7 measured |
| LMArena Text | 1489 | 1405 | Gemini 3.7 Flash |
| LMArena Text: instruction following | 1484 | 1405 | Gemini 3.7 Flash |
| LMArena Text: creative writing | 1488 | 1354 | Gemini 3.7 Flash |
| LMArena Vision | 1314 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: English | 1483 | 1426 | Gemini 3.7 Flash |
| LMArena Text: non-English | 1487 | 1382 | Gemini 3.7 Flash |
| LMArena Text: Chinese | 1552 | 1442 | Gemini 3.7 Flash |
| LMArena Text: German | 1506 | 1398 | Gemini 3.7 Flash |
| LMArena Text: Japanese | 1511 | 1260 | Gemini 3.7 Flash |
| LMArena Text: Korean | 1481 | 1314 | Gemini 3.7 Flash |
| LMArena Text: French | 1500 | 1424 | Gemini 3.7 Flash |
| LMArena Text: Spanish | 1495 | 1402 | Gemini 3.7 Flash |
| LMArena Text: Russian | 1515 | 1383 | Gemini 3.7 Flash |
| LMArena Text: Polish | 1503 | 1387 | Gemini 3.7 Flash |
| LMArena Text: multi-turn | 1485 | 1412 | Gemini 3.7 Flash |
| LMArena Text: longer queries | 1492 | 1418 | Gemini 3.7 Flash |
| LMArena Text: writing and language | 1491 | 1376 | Gemini 3.7 Flash |
| LMArena Text: entertainment and media | 1477 | 1360 | Gemini 3.7 Flash |
| LMArena Vision: English | 1309 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: Chinese | 1394 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: reading text | 1322 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: humor | 1299 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Vision: creative writing | 1312 | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.7 Flash | MiniMax M2.7 | 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
MiniMax M2.7 costs less
Repository review
50K input + 3K output tokens
MiniMax M2.7 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2.7 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 | Google Gemini 3.7 Flash | MiniMax M2.7 |
|---|---|---|
| Maker | MiniMax | |
| Weights | No public weights listed | Open weights |
| Released | August 13, 2026 | March 18, 2026 |
| Context window | 1.05M | 205K |
| Input $/Mtok | $0.75 | $0.30 |
| Output $/Mtok | $3.75 | $1.20 |
| Coding index | 69.9 | 28.4 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $1.78 | $0.64 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.7 Flash better than MiniMax M2.7 for coding?
Pick Gemini 3.7 Flash for coding: it scores 69.9 on the Vibe Coding Index against 28.4 for MiniMax M2.7. Pick MiniMax M2.7 when output tokens cost 3.1x less, or when a solved task costs $0.64 against $1.78.
Which is cheaper, Gemini 3.7 Flash or MiniMax M2.7?
Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Per solved SWE-bench Verified task, Gemini 3.7 Flash costs $1.78 and MiniMax M2.7 $0.64.
Which has the bigger context window, Gemini 3.7 Flash or MiniMax M2.7?
Gemini 3.7 Flash, with 1.05M tokens against 205K.
How many benchmarks is the Gemini 3.7 Flash vs MiniMax M2.7 comparison based on?
64 benchmarks have a result for both models as of October 21, 2026. Gemini 3.7 Flash's coding index rests on 2 independent benchmarks and MiniMax M2.7's on 1. Where only one model has a result, the page says so instead of naming a winner.