GPT-5 Pro vs MiniMax M2
MiniMax M2 costs 117.6x less per output token than GPT-5 Pro ($1.02 vs $120.00 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
GPT-5 Pro or MiniMax M2: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5 Pro for a larger context window (400K against 205K tokens).
- Shared results
- 1
- GPT-5 Pro only
- 8
- MiniMax M2 only
- 49
- Like-for-like categories
- 1 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only MiniMax M2 has a AA Intelligence Index result, 18.6.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M2 has a Design Arena: websites result, 1143.
Directional only
Long documents
Listed context window
GPT-5 Pro
GPT-5 Pro takes 400K tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2
GPT-5 Pro $0.075, MiniMax M2 $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2 has the number, $0.702.
Directional only
At a glance
- Coding index
- GPT-5 Pro not benchmarked, MiniMax M2 not benchmarked.
- Widest category
- Reasoning, 19.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Kagi LLM Benchmark: GPT-5 Pro 76.8% against MiniMax M2 57.8%, 19.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5 Pro $120.00 against MiniMax M2 $1.02 per million output tokens, 117.6x apart.
- Context window
- GPT-5 Pro takes 400K tokens, MiniMax M2 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 | GPT-5 Pro | Bars | MiniMax M2 | Ties |
|---|---|---|---|---|
| Reasoning | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards, none shared
| Benchmark | GPT-5 Pro | MiniMax M2 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 61.0% | Only MiniMax M2 measured |
| LMArena WebDev | Not measured | 1297 | Only MiniMax M2 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 82.6% | Only MiniMax M2 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 25.8% | Only MiniMax M2 measured |
| Terminal-Bench | Not measured | 30.0% | Only MiniMax M2 measured |
| WeirdML | 60.4% | Not measured | Only GPT-5 Pro measured |
| LMArena Text: coding | Not measured | 1371 | Only MiniMax M2 measured |
| LMArena Text: software and IT | Not measured | 1373 | Only MiniMax M2 measured |
| LMArena WebDev: HTML | Not measured | 1306 | Only MiniMax M2 measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5 Pro | MiniMax M2 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 18.6 | Only MiniMax M2 measured |
| Epoch Capabilities Index | 150.6 | Not measured | Only GPT-5 Pro measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5 Pro | MiniMax M2 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 86.8% | Only MiniMax M2 measured |
| Vending-Bench 2 | Not measured | $161 | Only MiniMax M2 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5 Pro | MiniMax M2 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 77.7% | Only MiniMax M2 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 13.7% | Only MiniMax M2 measured |
| ARC-AGI | 70.2% | Not measured | Only GPT-5 Pro measured |
| ARC-AGI-2 | 18.3% | Not measured | Only GPT-5 Pro measured |
| SimpleBench | 61.6% | Not measured | Only GPT-5 Pro measured |
| Chess puzzles | 48.0% | Not measured | Only GPT-5 Pro measured |
| LMArena Text: hard prompts | Not measured | 1357 | Only MiniMax M2 measured |
| LMArena Text: expert | Not measured | 1338 | Only MiniMax M2 measured |
| LMArena Text: hard prompts in English | Not measured | 1376 | Only MiniMax M2 measured |
| Kagi LLM Benchmark | 76.8% | 57.8% | GPT-5 Pro |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5 Pro | MiniMax M2 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 78.3 | Only MiniMax M2 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 78.3% | Only MiniMax M2 measured |
| FrontierMath, tiers 1 to 3 | 55.8% | Not measured | Only GPT-5 Pro measured |
| FrontierMath, tier 4 | 19.5% | Not measured | Only GPT-5 Pro measured |
| LMArena Text: math | Not measured | 1351 | Only MiniMax M2 measured |
| LMArena Text: mathematical work | Not measured | 1368 | Only MiniMax M2 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GPT-5 Pro | MiniMax M2 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 82.0% | Only MiniMax M2 measured |
| LMArena Text: science | Not measured | 1348 | Only MiniMax M2 measured |
| LMArena Text: medicine and healthcare | Not measured | 1367 | Only MiniMax M2 measured |
| LMArena Text: legal and government | Not measured | 1349 | Only MiniMax M2 measured |
| LMArena Text: business and finance | Not measured | 1336 | Only MiniMax M2 measured |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-5 Pro | MiniMax M2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1143 | Only MiniMax M2 measured |
| Design Arena: UI components | Not measured | 1137 | Only MiniMax M2 measured |
| Design Arena: game dev | Not measured | 1118 | Only MiniMax M2 measured |
| Design Arena: data viz | Not measured | 1140 | Only MiniMax M2 measured |
| Design Arena: 3D | Not measured | 1098 | Only MiniMax M2 measured |
| Design Arena: all code categories | Not measured | 1135 | Only MiniMax M2 measured |
| Design Arena: SVG | Not measured | 1100 | Only MiniMax M2 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | GPT-5 Pro | MiniMax M2 | Leader |
|---|---|---|---|
| IFBench | Not measured | 72.3% | Only MiniMax M2 measured |
| Long context reasoning (AA-LCR) | Not measured | 64.3% | Only MiniMax M2 measured |
| LMArena Text | Not measured | 1340 | Only MiniMax M2 measured |
| LMArena Text: instruction following | Not measured | 1329 | Only MiniMax M2 measured |
| LMArena Text: creative writing | Not measured | 1286 | Only MiniMax M2 measured |
| LMArena Text: English | Not measured | 1364 | Only MiniMax M2 measured |
| LMArena Text: non-English | Not measured | 1313 | Only MiniMax M2 measured |
| LMArena Text: Chinese | Not measured | 1366 | Only MiniMax M2 measured |
| LMArena Text: German | Not measured | 1357 | Only MiniMax M2 measured |
| LMArena Text: French | Not measured | 1336 | Only MiniMax M2 measured |
| LMArena Text: Spanish | Not measured | 1326 | Only MiniMax M2 measured |
| LMArena Text: Russian | Not measured | 1330 | Only MiniMax M2 measured |
| LMArena Text: Polish | Not measured | 1312 | Only MiniMax M2 measured |
| LMArena Text: multi-turn | Not measured | 1361 | Only MiniMax M2 measured |
| LMArena Text: longer queries | Not measured | 1331 | Only MiniMax M2 measured |
| LMArena Text: writing and language | Not measured | 1295 | Only MiniMax M2 measured |
| LMArena Text: entertainment and media | Not measured | 1298 | Only MiniMax M2 measured |
| Neither model has a result on the other 29 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5 Pro | MiniMax M2 | 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 costs less
Repository review
50K input + 3K output tokens
MiniMax M2 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2 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 Pro | MiniMax M2 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2025 | October 23, 2025 |
| Context window | 400K | 205K |
| Input $/Mtok | $15.00 | $0.255 |
| Output $/Mtok | $120.00 | $1.02 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | $0.702 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Pro better than MiniMax M2 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5 Pro for a larger context window (400K against 205K tokens).
Which is cheaper, GPT-5 Pro or MiniMax M2?
GPT-5 Pro costs $15.00 per million input tokens and $120.00 per million output tokens; MiniMax M2 costs $0.255 and $1.02. Cost per solved task is known for MiniMax M2 only.
Which has the bigger context window, GPT-5 Pro or MiniMax M2?
GPT-5 Pro, with 400K tokens against 205K.
How many benchmarks is the GPT-5 Pro vs MiniMax M2 comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. GPT-5 Pro's coding index rests on 0 independent benchmarks and MiniMax M2's on 1. Where only one model has a result, the page says so instead of naming a winner.