GPT-5.5 Pro vs MiniMax M1
MiniMax M1 costs 81.8x less per output token than GPT-5.5 Pro ($2.20 vs $180.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $180.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $2.20
GPT-5.5 Pro or MiniMax M1: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.5 Pro for a larger context window (1.05M against 1M tokens).
No benchmark has tested both yet. GPT-5.5 Pro has results on Epoch Capabilities Index, ARC-AGI and ARC-AGI-2; MiniMax M1 on LMArena Text: coding, LMArena Text: software and IT and AA Intelligence Index. Compare them on price and context instead.
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 M1 has a AA Intelligence Index result, 11.7.
Directional only
Long documents
Listed context window
GPT-5.5 Pro
GPT-5.5 Pro takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M1
GPT-5.5 Pro $0.120, MiniMax M1 $0.0015 per turn.
List prices
At a glance
- Coding index
- GPT-5.5 Pro not benchmarked, MiniMax M1 not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-5.5 Pro $180.00 against MiniMax M1 $2.20 per million output tokens, 81.8x apart.
- Context window
- GPT-5.5 Pro takes 1.05M tokens, MiniMax M1 1M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards measured
| Benchmark | GPT-5.5 Pro | MiniMax M1 | Leader |
|---|---|---|---|
| LMArena Text: coding | Not measured | 1359 | Only MiniMax M1 measured |
| LMArena Text: software and IT | Not measured | 1359 | Only MiniMax M1 measured |
| Neither model has a result on the other 41 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5.5 Pro | MiniMax M1 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 11.7 | Only MiniMax M1 measured |
| Epoch Capabilities Index | 162.9 | Not measured | Only GPT-5.5 Pro measured |
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | GPT-5.5 Pro | MiniMax M1 | Leader |
|---|---|---|---|
| ARC-AGI | 96.5% | Not measured | Only GPT-5.5 Pro measured |
| ARC-AGI-2 | 84.6% | Not measured | Only GPT-5.5 Pro measured |
| SimpleBench | 76.9% | Not measured | Only GPT-5.5 Pro measured |
| Chess puzzles | 62.0% | Not measured | Only GPT-5.5 Pro measured |
| LMArena Text: hard prompts | Not measured | 1339 | Only MiniMax M1 measured |
| LMArena Text: expert | Not measured | 1317 | Only MiniMax M1 measured |
| LMArena Text: hard prompts in English | Not measured | 1353 | Only MiniMax M1 measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | GPT-5.5 Pro | MiniMax M1 | Leader |
|---|---|---|---|
| FrontierMath, tiers 1 to 3 | 87.7% | Not measured | Only GPT-5.5 Pro measured |
| FrontierMath, tier 4 | 78.0% | Not measured | Only GPT-5.5 Pro measured |
| LMArena Text: math | Not measured | 1361 | Only MiniMax M1 measured |
| LMArena Text: mathematical work | Not measured | 1363 | Only MiniMax M1 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | GPT-5.5 Pro | MiniMax M1 | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1354 | Only MiniMax M1 measured |
| LMArena Text: medicine and healthcare | Not measured | 1355 | Only MiniMax M1 measured |
| LMArena Text: legal and government | Not measured | 1337 | Only MiniMax M1 measured |
| LMArena Text: business and finance | Not measured | 1319 | Only MiniMax M1 measured |
| Neither model has a result on the other 16 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards measured
| Benchmark | GPT-5.5 Pro | MiniMax M1 | Leader |
|---|---|---|---|
| DTBench | 96.0% | Not measured | Only GPT-5.5 Pro measured |
| LMCA | 53.9% | Not measured | Only GPT-5.5 Pro measured |
| LMArena Text | Not measured | 1343 | Only MiniMax M1 measured |
| LMArena Text: instruction following | Not measured | 1312 | Only MiniMax M1 measured |
| LMArena Text: creative writing | Not measured | 1297 | Only MiniMax M1 measured |
| LMArena Text: English | Not measured | 1363 | Only MiniMax M1 measured |
| LMArena Text: non-English | Not measured | 1319 | Only MiniMax M1 measured |
| LMArena Text: Chinese | Not measured | 1360 | Only MiniMax M1 measured |
| LMArena Text: German | Not measured | 1350 | Only MiniMax M1 measured |
| LMArena Text: Japanese | Not measured | 1217 | Only MiniMax M1 measured |
| LMArena Text: Korean | Not measured | 1266 | Only MiniMax M1 measured |
| LMArena Text: French | Not measured | 1370 | Only MiniMax M1 measured |
| LMArena Text: Spanish | Not measured | 1353 | Only MiniMax M1 measured |
| LMArena Text: Russian | Not measured | 1329 | Only MiniMax M1 measured |
| LMArena Text: Polish | Not measured | 1329 | Only MiniMax M1 measured |
| LMArena Text: multi-turn | Not measured | 1335 | Only MiniMax M1 measured |
| LMArena Text: longer queries | Not measured | 1326 | Only MiniMax M1 measured |
| LMArena Text: writing and language | Not measured | 1311 | Only MiniMax M1 measured |
| LMArena Text: entertainment and media | Not measured | 1303 | Only MiniMax M1 measured |
| Neither model has a result on the other 29 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 M1 costs less
Repository review
50K input + 3K output tokens
MiniMax M1 costs less
Agent loop
200K input + 10K output tokens
MiniMax M1 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-5.5 Pro | MiniMax M1 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | No public weights listed |
| Released | April 24, 2026 | June 17, 2025 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $30.00 | $0.40 |
| Output $/Mtok | $180.00 | $2.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.5 Pro better than MiniMax M1 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.5 Pro for a larger context window (1.05M against 1M tokens).
Which is cheaper, GPT-5.5 Pro or MiniMax M1?
GPT-5.5 Pro costs $30.00 per million input tokens and $180.00 per million output tokens; MiniMax M1 costs $0.40 and $2.20. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.5 Pro or MiniMax M1?
GPT-5.5 Pro, with 1.05M tokens against 1M.
Has any benchmark tested both GPT-5.5 Pro and MiniMax M1?
No benchmark has tested both yet. GPT-5.5 Pro has results on Epoch Capabilities Index, ARC-AGI and ARC-AGI-2; MiniMax M1 on LMArena Text: coding, LMArena Text: software and IT and AA Intelligence Index. Compare them on price and context instead. Data as of October 22, 2026.