GPT-3.5 Turbo (older v0613) vs MiniMax M1
GPT-3.5 Turbo (older v0613) and MiniMax M1 cost about the same per output token ($2.00 vs $2.20 per million). Updated October 23, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $2.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $2.20
GPT-3.5 Turbo (older v0613) or MiniMax M1: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-3.5 Turbo (older v0613) for output tokens 1.1x cheaper ($2.00 vs $2.20 per million).
No benchmark has tested both yet. GPT-3.5 Turbo (older v0613) has results on GSM8K, MMLU and WinoGrande; 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 4K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M1
GPT-3.5 Turbo (older v0613) $0.0020, MiniMax M1 $0.0015 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo (older v0613) 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-3.5 Turbo (older v0613) $2.00 against MiniMax M1 $2.20 per million output tokens, 1.1x apart.
- Context window
- GPT-3.5 Turbo (older v0613) takes 4K 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-3.5 Turbo (older v0613) | 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 index1 board measured
| Benchmark | GPT-3.5 Turbo (older v0613) | 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 | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | 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 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | MiniMax M1 | Leader |
|---|---|---|---|
| GSM8K | 46.9% | Not measured | Only GPT-3.5 Turbo (older v0613) 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 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | MiniMax M1 | Leader |
|---|---|---|---|
| MMLU | 68.9% | Not measured | Only GPT-3.5 Turbo (older v0613) measured |
| 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 15 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index18 boards measured
| Benchmark | GPT-3.5 Turbo (older v0613) | MiniMax M1 | Leader |
|---|---|---|---|
| WinoGrande | 81.6% | Not measured | Only GPT-3.5 Turbo (older v0613) 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 | 1218 | 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 30 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-3.5 Turbo (older v0613) | MiniMax M1 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | No public weights listed |
| Released | January 25, 2024 | June 17, 2025 |
| Context window | 4K | 1M |
| Input $/Mtok | $1.00 | $0.40 |
| Output $/Mtok | $2.00 | $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-3.5 Turbo (older v0613) better than MiniMax M1 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo (older v0613) for output tokens 1.1x cheaper ($2.00 vs $2.20 per million).
Which is cheaper, GPT-3.5 Turbo (older v0613) or MiniMax M1?
GPT-3.5 Turbo (older v0613) costs $1.00 per million input tokens and $2.00 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-3.5 Turbo (older v0613) or MiniMax M1?
MiniMax M1, with 1M tokens against 4K.
Has any benchmark tested both GPT-3.5 Turbo (older v0613) and MiniMax M1?
No benchmark has tested both yet. GPT-3.5 Turbo (older v0613) has results on GSM8K, MMLU and WinoGrande; 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 23, 2026.