GPT-5.1-Codex-Max vs MiniMax M1
MiniMax M1 costs 4.5x less per output token than GPT-5.1-Codex-Max ($2.20 vs $10.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $10.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $2.20
GPT-5.1-Codex-Max or MiniMax M1: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. GPT-5.1-Codex-Max has results on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench; 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
MiniMax M1
MiniMax M1 takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M1
GPT-5.1-Codex-Max $0.0063, MiniMax M1 $0.0015 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Max 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-5.1-Codex-Max $10.00 against MiniMax M1 $2.20 per million output tokens, 4.5x apart.
- Context window
- GPT-5.1-Codex-Max takes 400K 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 Index6 boards measured
| Benchmark | GPT-5.1-Codex-Max | MiniMax M1 | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | 83.6% | Not measured | Only GPT-5.1-Codex-Max measured |
| Vibe Code Bench (Vals AI) | 22.2% | Not measured | Only GPT-5.1-Codex-Max measured |
| Terminal-Bench | 60.4% | Not measured | Only GPT-5.1-Codex-Max measured |
| ALE-Bench | 1228.3 | Not measured | Only GPT-5.1-Codex-Max measured |
| 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 33 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.1-Codex-Max | MiniMax M1 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 11.7 | Only MiniMax M1 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.1-Codex-Max | MiniMax M1 | Leader |
|---|---|---|---|
| METR time horizons | 70.8% | Not measured | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-5.1-Codex-Max | MiniMax M1 | Leader |
|---|---|---|---|
| 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 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-5.1-Codex-Max | MiniMax M1 | Leader |
|---|---|---|---|
| ProofBench | 9.0% | Not measured | Only GPT-5.1-Codex-Max 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-5.1-Codex-Max | 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 14 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index17 boards measured
| Benchmark | GPT-5.1-Codex-Max | MiniMax M1 | Leader |
|---|---|---|---|
| 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-5.1-Codex-Max | MiniMax M1 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | No public weights listed |
| Released | December 4, 2025 | June 17, 2025 |
| Context window | 400K | 1M |
| Input $/Mtok | $1.25 | $0.40 |
| Output $/Mtok | $10.00 | $2.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex-Max better than MiniMax M1 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-5.1-Codex-Max or MiniMax M1?
GPT-5.1-Codex-Max costs $1.25 per million input tokens and $10.00 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-5.1-Codex-Max or MiniMax M1?
MiniMax M1, with 1M tokens against 400K.
Has any benchmark tested both GPT-5.1-Codex-Max and MiniMax M1?
No benchmark has tested both yet. GPT-5.1-Codex-Max has results on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench; 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.