GPT-5 Mini vs MiniMax M3.1 Flash
MiniMax M3.1 Flash leads GPT-5 Mini on coding, 59.0 to 34.2 on the Vibe Coding Index, and MiniMax M3.1 Flash costs 3.3x less per output token ($0.60 vs $2.00 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
GPT-5 Mini or MiniMax M3.1 Flash: which to pick
Pick MiniMax M3.1 Flash for coding: it scores 59.0 on the Vibe Coding Index against 34.2 for GPT-5 Mini.
GPT-5 Mini is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 5
- GPT-5 Mini only
- 98
- MiniMax M3.1 Flash only
- 15
- Like-for-like categories
- 4 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
MiniMax M3.1 Flash
MiniMax M3.1 Flash scores 59.0 against 34.2.
2 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiniMax M3.1 Flash
MiniMax M3.1 Flash leads, 42.7 against 20.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5 Mini has a GPQA Diamond result, 80.3%.
Directional only
Math
AIME
No call
Only GPT-5 Mini has a AIME result, 91.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5 Mini has a MMLU Pro result, 82.2%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5 Mini has a Design Arena: websites result, 1125.
Directional only
General
Vals Index
No call
Only MiniMax M3.1 Flash has a Vals Index result, 53.8%.
Directional only
Long documents
Listed context window
MiniMax M3.1 Flash
MiniMax M3.1 Flash takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M3.1 Flash
GPT-5 Mini $0.0013, MiniMax M3.1 Flash $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 Mini has the number, $0.08.
Directional only
At a glance
- Coding index
- GPT-5 Mini 34.2 from 2 benchmarks, MiniMax M3.1 Flash 59.0 from 4 benchmarks.
- Widest category
- Coding, 37.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-5 Mini 14.2% against MiniMax M3.1 Flash 73.9%, 59.8 points apart on a 0 to 100 scale.
- Output price
- GPT-5 Mini $2.00 against MiniMax M3.1 Flash $0.60 per million output tokens, 3.3x apart.
- Context window
- GPT-5 Mini takes 400K tokens, MiniMax M3.1 Flash 1M.
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-5 Mini | Bars | MiniMax M3.1 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GPT-5 Mini | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| SWE-bench Verified | 59.8% | Not measured | Only GPT-5 Mini measured |
| SWE-bench Multilingual | 39.7% | Not measured | Only GPT-5 Mini measured |
| LiveBench coding | Not measured | 83.9% | Only MiniMax M3.1 Flash measured |
| LMArena WebDev | Not measured | 1587 | Only MiniMax M3.1 Flash measured |
| LiveCodeBench (Vals AI) | 86.6% | Not measured | Only GPT-5 Mini measured |
| SWE-bench Verified (Vals AI) | 60.8% | Not measured | Only GPT-5 Mini measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 25.3% | Only MiniMax M3.1 Flash measured |
| Vibe Code Bench (Vals AI) | 14.2% | 73.9% | MiniMax M3.1 Flash |
| LiveCodeBench (Artificial Analysis run) | 83.8% | Not measured | Only GPT-5 Mini measured |
| SciCode | 39.0% | 53.4% | MiniMax M3.1 Flash |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only GPT-5 Mini measured |
| Terminal-Bench | 34.8% | Not measured | Only GPT-5 Mini measured |
| WeirdML | 52.7% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: coding | 1406 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: software and IT | 1394 | Not measured | Only GPT-5 Mini measured |
| LMArena WebDev: React | Not measured | 1609 | Only MiniMax M3.1 Flash measured |
| LMArena WebDev: HTML | Not measured | 1529 | Only MiniMax M3.1 Flash measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5 Mini | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.6 | 42.7 | MiniMax M3.1 Flash |
| Epoch Capabilities Index | 145.3 | Not measured | Only GPT-5 Mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-5 Mini | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 72.7% | Only MiniMax M3.1 Flash measured |
| LiveBench browser | Not measured | 92.0% | Only MiniMax M3.1 Flash measured |
| LiveBench long agentic | Not measured | 34.7% | Only MiniMax M3.1 Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.1% | Only MiniMax M3.1 Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 34.1% | Only MiniMax M3.1 Flash measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 7.5% | Only MiniMax M3.1 Flash measured |
| τ²-Bench Telecom | 71.1% | Not measured | Only GPT-5 Mini measured |
| Vending-Bench 2 | -$31 | Not measured | Only GPT-5 Mini measured |
| Berkeley Function Calling Leaderboard (BFCL) | 55.5% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5 Mini | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | 80.3% | Not measured | Only GPT-5 Mini measured |
| LiveBench reasoning | Not measured | 82.9% | Only MiniMax M3.1 Flash measured |
| MMMU Pro (Vals AI) | 78.9% | Not measured | Only GPT-5 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 82.8% | Not measured | Only GPT-5 Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 21.5% | 48.0% | MiniMax M3.1 Flash |
| GPQA Diamond (Epoch AI run) | 75.0% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI | 54.3% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI-2 | 4.4% | Not measured | Only GPT-5 Mini measured |
| Chess puzzles | 24.0% | Not measured | Only GPT-5 Mini measured |
| Mystery game puzzles | 10.0% | Not measured | Only GPT-5 Mini measured |
| VPCT | 40.2% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts | 1380 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: expert | 1379 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts in English | 1383 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: diagrams | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: homework | 1210 | Not measured | Only GPT-5 Mini measured |
| Kagi LLM Benchmark | 70.3% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | GPT-5 Mini | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| AIME | 91.5% | Not measured | Only GPT-5 Mini measured |
| MATH 500 (Vals AI) | 94.8% | Not measured | Only GPT-5 Mini measured |
| MGSM (Vals AI) | 92.6% | Not measured | Only GPT-5 Mini measured |
| AA Math Index | 90.7 | Not measured | Only GPT-5 Mini measured |
| AIME 2025 (Artificial Analysis run) | 90.7% | Not measured | Only GPT-5 Mini measured |
| OTIS Mock AIME | 86.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tiers 1 to 3 | 46.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5 Mini measured |
| ProofBench | 9.0% | Not measured | Only GPT-5 Mini measured |
| MATH level 5 | 97.8% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: math | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: mathematical work | 1380 | Not measured | Only GPT-5 Mini measured |
| MathArena | 14.8% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | GPT-5 Mini | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| MMLU Pro | 82.2% | Not measured | Only GPT-5 Mini measured |
| LegalBench (Vals AI) | 81.8% | Not measured | Only GPT-5 Mini measured |
| CaseLaw (Vals AI) | 68.5% | Not measured | Only GPT-5 Mini measured |
| CorpFin (Vals AI) | 60.2% | Not measured | Only GPT-5 Mini measured |
| TaxEval (Vals AI) | 75.2% | Not measured | Only GPT-5 Mini measured |
| MortgageTax (Vals AI) | 66.9% | Not measured | Only GPT-5 Mini measured |
| MedQA (Vals AI) | 96.1% | Not measured | Only GPT-5 Mini measured |
| MedCode (Vals AI) | 43.0% | Not measured | Only GPT-5 Mini measured |
| MMLU Pro (Artificial Analysis run) | 83.7% | Not measured | Only GPT-5 Mini measured |
| SimpleQA Verified | 21.6% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: science | 1371 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: medicine and healthcare | 1380 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: legal and government | 1375 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: business and finance | 1358 | Not measured | Only GPT-5 Mini measured |
| FACTS Benchmark Suite | 38.6% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-5 Mini | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1125 | Not measured | Only GPT-5 Mini measured |
| Design Arena: UI components | 1103 | Not measured | Only GPT-5 Mini measured |
| Design Arena: game dev | 1129 | Not measured | Only GPT-5 Mini measured |
| Design Arena: data viz | 1131 | Not measured | Only GPT-5 Mini measured |
| Design Arena: 3D | 1036 | Not measured | Only GPT-5 Mini measured |
| Design Arena: all code categories | 1114 | Not measured | Only GPT-5 Mini measured |
| Design Arena: SVG | 1090 | Not measured | Only GPT-5 Mini measured |
| Design Arena: ASCII art | 1125 | Not measured | Only GPT-5 Mini measured |
| LiveBench design | Not measured | 74.0% | Only MiniMax M3.1 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5 Mini | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| Vals Index | Not measured | 53.8% | Only MiniMax M3.1 Flash measured |
| LiveBench data analysis | Not measured | 71.4% | Only MiniMax M3.1 Flash measured |
| SAGE (Vals AI) | 43.0% | Not measured | Only GPT-5 Mini measured |
| MedScribe (Vals AI) | 80.6% | Not measured | Only GPT-5 Mini measured |
| IFBench | 75.4% | Not measured | Only GPT-5 Mini measured |
| Long context reasoning (AA-LCR) | 72.3% | 79.7% | MiniMax M3.1 Flash |
| DTBench | 80.5% | Not measured | Only GPT-5 Mini measured |
| LMCA | 34.2% | Not measured | Only GPT-5 Mini measured |
| Fiction.LiveBench | 69.4% | Not measured | Only GPT-5 Mini measured |
| Creative writing (Lech Mazur) | 83.1% | Not measured | Only GPT-5 Mini measured |
| LMArena Text | 1373 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: instruction following | 1357 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: creative writing | 1325 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: English | 1379 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: non-English | 1363 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Chinese | 1386 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: German | 1366 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Japanese | 1341 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Korean | 1308 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: French | 1386 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Spanish | 1354 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Russian | 1362 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Polish | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: multi-turn | 1363 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: longer queries | 1355 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: writing and language | 1344 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: entertainment and media | 1340 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: English | 1216 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: Chinese | 1214 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: reading text | 1199 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: humor | 1205 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: captioning | 1217 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: recognizing things | 1226 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: creative writing | 1181 | Not measured | Only GPT-5 Mini measured |
| MultiChallenge | 59.0% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5 Mini | MiniMax M3.1 Flash | 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 M3.1 Flash costs less
Repository review
50K input + 3K output tokens
MiniMax M3.1 Flash costs less
Agent loop
200K input + 10K output tokens
MiniMax M3.1 Flash 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-5 Mini | MiniMax M3.1 Flash |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | No public weights listed |
| Released | August 7, 2025 | October 19, 2026 |
| Context window | 400K | 1M |
| Input $/Mtok | $0.25 | $0.15 |
| Output $/Mtok | $2.00 | $0.60 |
| Coding index | 34.2 | 59.0 |
| Independent measurements behind it | 2 | 4 |
| Cost per solved task | $0.08 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Mini better than MiniMax M3.1 Flash for coding?
Pick MiniMax M3.1 Flash for coding: it scores 59.0 on the Vibe Coding Index against 34.2 for GPT-5 Mini. GPT-5 Mini is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, GPT-5 Mini or MiniMax M3.1 Flash?
GPT-5 Mini costs $0.25 per million input tokens and $2.00 per million output tokens; MiniMax M3.1 Flash costs $0.15 and $0.60. Cost per solved task is known for GPT-5 Mini only.
Which has the bigger context window, GPT-5 Mini or MiniMax M3.1 Flash?
MiniMax M3.1 Flash, with 1M tokens against 400K.
How many benchmarks is the GPT-5 Mini vs MiniMax M3.1 Flash comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. GPT-5 Mini's coding index rests on 2 independent benchmarks and MiniMax M3.1 Flash's on 4. Where only one model has a result, the page says so instead of naming a winner.