GPT-3.5 Turbo vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads GPT-3.5 Turbo on the Artificial Analysis Intelligence Index, 46.3 to 5.5, and MiMo-V2.6-Pro costs 1.7x less per output token ($0.87 vs $1.50 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
GPT-3.5 Turbo or MiMo-V2.6-Pro: which to pick
Only MiMo-V2.6-Pro has a coding score, 65.4 on the Vibe Coding Index; GPT-3.5 Turbo has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 1
- GPT-3.5 Turbo only
- 12
- MiMo-V2.6-Pro only
- 72
- 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
Only MiMo-V2.6-Pro has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 46.3 against 5.5.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-3.5 Turbo has a GPQA Diamond result, 30.6%.
Directional only
Web design
Design Arena: websites
No call
Only MiMo-V2.6-Pro has a Design Arena: websites result, 1307.
Directional only
General
Vals Index
No call
Only MiMo-V2.6-Pro has a Vals Index result, 57.8%.
Directional only
Long documents
Listed context window
MiMo-V2.6-Pro
MiMo-V2.6-Pro takes 1.05M tokens against 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.6-Pro
GPT-3.5 Turbo $0.0013, MiMo-V2.6-Pro $0.0009 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo not benchmarked, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
- Widest category
- Intelligence, 40.8 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: GPT-3.5 Turbo 5.5 against MiMo-V2.6-Pro 46.3, 40.8 points apart on a 0 to 100 scale.
- Output price
- GPT-3.5 Turbo $1.50 against MiMo-V2.6-Pro $0.87 per million output tokens, 1.7x apart.
- Context window
- GPT-3.5 Turbo takes 16K tokens, MiMo-V2.6-Pro 1.05M.
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-3.5 Turbo | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index19 boards, none shared
| Benchmark | GPT-3.5 Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 81.5% | Only MiMo-V2.6-Pro measured |
| LMArena WebDev | Not measured | 1625 | Only MiMo-V2.6-Pro measured |
| AA Coding Index | 10.7 | Not measured | Only GPT-3.5 Turbo measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 31.3% | Only MiMo-V2.6-Pro measured |
| Vibe Code Bench (Vals AI) | Not measured | 85.2% | Only MiMo-V2.6-Pro measured |
| Code migration (Vals AI) | Not measured | 43.0% | Only MiMo-V2.6-Pro measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only MiMo-V2.6-Pro measured |
| IOI (Vals AI) | Not measured | 39.3% | Only MiMo-V2.6-Pro measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.8% | Only MiMo-V2.6-Pro measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 41.3% | Only MiMo-V2.6-Pro measured |
| CyberBench (Vals AI) | Not measured | 72.9% | Only MiMo-V2.6-Pro measured |
| SciCode | Not measured | 60.9% | Only MiMo-V2.6-Pro measured |
| ALE-Bench | Not measured | 1158.1 | Only MiMo-V2.6-Pro measured |
| LMArena Text: coding | Not measured | 1533 | Only MiMo-V2.6-Pro measured |
| LMArena Text: software and IT | Not measured | 1528 | Only MiMo-V2.6-Pro measured |
| LMArena WebDev: React | Not measured | 1639 | Only MiMo-V2.6-Pro measured |
| LMArena WebDev: HTML | Not measured | 1616 | Only MiMo-V2.6-Pro measured |
| LMArena WebDev: from an image | Not measured | 1598 | Only MiMo-V2.6-Pro measured |
| SciCode | 0.0% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.5 | 46.3 | MiMo-V2.6-Pro |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-3.5 Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1290 | Only MiMo-V2.6-Pro measured |
| LiveBench research | Not measured | 76.7% | Only MiMo-V2.6-Pro measured |
| LiveBench browser | Not measured | 88.0% | Only MiMo-V2.6-Pro measured |
| LiveBench long agentic | Not measured | 47.5% | Only MiMo-V2.6-Pro measured |
| SREBench (Vals AI) | Not measured | 3.0% | Only MiMo-V2.6-Pro measured |
| Finance Agent (Vals AI) | Not measured | 57.3% | Only MiMo-V2.6-Pro measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.4% | Only MiMo-V2.6-Pro measured |
| Legal Research Bench (Vals AI) | Not measured | 47.1% | Only MiMo-V2.6-Pro measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 13.8% | Only MiMo-V2.6-Pro measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 62.9% | Only MiMo-V2.6-Pro measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 2.9% | Only MiMo-V2.6-Pro measured |
| APEX-Agents | Not measured | 54.4% | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | GPT-3.5 Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 30.6% | Not measured | Only GPT-3.5 Turbo measured |
| LiveBench reasoning | Not measured | 79.6% | Only MiMo-V2.6-Pro measured |
| MysteryMechanism (Vals AI) | Not measured | 15.3% | Only MiMo-V2.6-Pro measured |
| GPQA Diamond (Artificial Analysis run) | 29.7% | Not measured | Only GPT-3.5 Turbo measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 49.4% | Only MiMo-V2.6-Pro measured |
| BIG-Bench Hard | 61.6% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: hard prompts | Not measured | 1511 | Only MiMo-V2.6-Pro measured |
| LMArena Text: expert | Not measured | 1541 | Only MiMo-V2.6-Pro measured |
| LMArena Text: hard prompts in English | Not measured | 1520 | Only MiMo-V2.6-Pro measured |
| LMArena Vision: diagrams | Not measured | 1281 | Only MiMo-V2.6-Pro measured |
| LMArena Vision: homework | Not measured | 1264 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-3.5 Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| ProofBench | Not measured | 70.0% | Only MiMo-V2.6-Pro measured |
| GSM8K | 57.8% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: math | Not measured | 1500 | Only MiMo-V2.6-Pro measured |
| LMArena Text: mathematical work | Not measured | 1511 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-3.5 Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 64.4% | Not measured | Only GPT-3.5 Turbo measured |
| MedQA (Vals AI) | 58.5% | Not measured | Only GPT-3.5 Turbo measured |
| MedCode (Vals AI) | Not measured | 45.0% | Only MiMo-V2.6-Pro measured |
| MMLU Pro (Artificial Analysis run) | 46.2% | Not measured | Only GPT-3.5 Turbo measured |
| MMLU | 68.5% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: science | Not measured | 1506 | Only MiMo-V2.6-Pro measured |
| LMArena Text: medicine and healthcare | Not measured | 1497 | Only MiMo-V2.6-Pro measured |
| LMArena Text: legal and government | Not measured | 1485 | Only MiMo-V2.6-Pro measured |
| LMArena Text: business and finance | Not measured | 1468 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-3.5 Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1307 | Only MiMo-V2.6-Pro measured |
| Design Arena: UI components | Not measured | 1337 | Only MiMo-V2.6-Pro measured |
| Design Arena: game dev | Not measured | 1313 | Only MiMo-V2.6-Pro measured |
| Design Arena: data viz | Not measured | 1337 | Only MiMo-V2.6-Pro measured |
| Design Arena: 3D | Not measured | 1329 | Only MiMo-V2.6-Pro measured |
| Design Arena: all code categories | Not measured | 1316 | Only MiMo-V2.6-Pro measured |
| LiveBench design | Not measured | 78.5% | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards, none shared
| Benchmark | GPT-3.5 Turbo | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Vals Index | Not measured | 57.8% | Only MiMo-V2.6-Pro measured |
| LiveBench data analysis | Not measured | 72.3% | Only MiMo-V2.6-Pro measured |
| Public Benefits Bench (Vals AI) | Not measured | 68.9% | Only MiMo-V2.6-Pro measured |
| SAGE (Vals AI) | Not measured | 45.0% | Only MiMo-V2.6-Pro measured |
| MedScribe (Vals AI) | Not measured | 88.3% | Only MiMo-V2.6-Pro measured |
| Long context reasoning (AA-LCR) | Not measured | 86.3% | Only MiMo-V2.6-Pro measured |
| DTBench | 48.5% | Not measured | Only GPT-3.5 Turbo measured |
| LMCA | 9.7% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text | Not measured | 1491 | Only MiMo-V2.6-Pro measured |
| LMArena Text: instruction following | Not measured | 1491 | Only MiMo-V2.6-Pro measured |
| LMArena Text: creative writing | Not measured | 1466 | Only MiMo-V2.6-Pro measured |
| LMArena Vision | Not measured | 1263 | Only MiMo-V2.6-Pro measured |
| LMArena Text: English | Not measured | 1504 | Only MiMo-V2.6-Pro measured |
| LMArena Text: non-English | Not measured | 1474 | Only MiMo-V2.6-Pro measured |
| LMArena Text: Chinese | Not measured | 1529 | Only MiMo-V2.6-Pro measured |
| LMArena Text: Russian | Not measured | 1479 | Only MiMo-V2.6-Pro measured |
| LMArena Text: multi-turn | Not measured | 1466 | Only MiMo-V2.6-Pro measured |
| LMArena Text: longer queries | Not measured | 1501 | Only MiMo-V2.6-Pro measured |
| LMArena Text: writing and language | Not measured | 1470 | Only MiMo-V2.6-Pro measured |
| LMArena Text: entertainment and media | Not measured | 1465 | Only MiMo-V2.6-Pro measured |
| LMArena Vision: English | Not measured | 1268 | Only MiMo-V2.6-Pro measured |
| LMArena Vision: reading text | Not measured | 1270 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | MiMo-V2.6-Pro | 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
MiMo-V2.6-Pro costs less
Repository review
50K input + 3K output tokens
MiMo-V2.6-Pro costs less
Agent loop
200K input + 10K output tokens
MiMo-V2.6-Pro 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 | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | OpenAI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | May 28, 2023 | September 21, 2026 |
| Context window | 16K | 1.05M |
| Input $/Mtok | $0.50 | $0.435 |
| Output $/Mtok | $1.50 | $0.87 |
| Coding index | Not benchmarked | 65.4 |
| Independent measurements behind it | 0 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-3.5 Turbo better than MiMo-V2.6-Pro for coding?
Only MiMo-V2.6-Pro has a coding score, 65.4 on the Vibe Coding Index; GPT-3.5 Turbo has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-3.5 Turbo or MiMo-V2.6-Pro?
GPT-3.5 Turbo costs $0.50 per million input tokens and $1.50 per million output tokens; MiMo-V2.6-Pro costs $0.435 and $0.87. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo or MiMo-V2.6-Pro?
MiMo-V2.6-Pro, with 1.05M tokens against 16K.
How many benchmarks is the GPT-3.5 Turbo vs MiMo-V2.6-Pro comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. GPT-3.5 Turbo's coding index rests on 0 independent benchmarks and MiMo-V2.6-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.