Qwen3 14B vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads Qwen3 14B on the Artificial Analysis Intelligence Index, 46.3 to 6.7, and Qwen3 14B costs 3.8x less per output token ($0.23 vs $0.87 per million). Updated October 22, 2026; 4 benchmarks have a result for both.
Qwen3 14B or MiMo-V2.6-Pro: which to pick
Only MiMo-V2.6-Pro has a coding score, 65.4 on the Vibe Coding Index; Qwen3 14B has none, so the two cannot be ranked on coding.
Pick Qwen3 14B for output tokens 3.8x cheaper ($0.23 vs $0.87 per million).
- Shared results
- 4
- Qwen3 14B only
- 16
- MiMo-V2.6-Pro only
- 69
- Like-for-like categories
- 4 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 6.7.
Same board, both measured
Web design
Design Arena: websites
No call
Only MiMo-V2.6-Pro has a Design Arena: websites result, 1308.
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 41K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 14B
Qwen3 14B $0.0002, MiMo-V2.6-Pro $0.0009 per turn.
List prices
At a glance
- Coding index
- Qwen3 14B not benchmarked, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
- Widest category
- General, 86.3 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Qwen3 14B 0.0% against MiMo-V2.6-Pro 86.3%, 86.3 points apart on a 0 to 100 scale.
- Output price
- Qwen3 14B $0.23 against MiMo-V2.6-Pro $0.87 per million output tokens, 3.8x apart.
- Context window
- Qwen3 14B takes 41K 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 | Qwen3 14B | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Qwen3 14B | 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 |
| 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 |
| LiveCodeBench (Artificial Analysis run) | 52.3% | Not measured | Only Qwen3 14B measured |
| SciCode | 30.7% | 60.9% | MiMo-V2.6-Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 5.3% | Not measured | Only Qwen3 14B 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 |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3 14B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 46.3 | MiMo-V2.6-Pro |
| Epoch Capabilities Index | 138.2 | Not measured | Only Qwen3 14B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Qwen3 14B | 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 |
| τ²-Bench Telecom | 34.5% | Not measured | Only Qwen3 14B measured |
| APEX-Agents | Not measured | 54.4% | Only MiMo-V2.6-Pro measured |
| Berkeley Function Calling Leaderboard (BFCL) | 41.0% | Not measured | Only Qwen3 14B measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3 14B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| 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) | 60.4% | Not measured | Only Qwen3 14B measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.5% | 49.4% | MiMo-V2.6-Pro |
| GPQA Diamond (Epoch AI run) | 63.8% | Not measured | Only Qwen3 14B 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 |
| Kagi LLM Benchmark | 49.1% | Not measured | Only Qwen3 14B measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Qwen3 14B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Math Index | 58.0 | Not measured | Only Qwen3 14B measured |
| AIME 2025 (Artificial Analysis run) | 58.0% | Not measured | Only Qwen3 14B measured |
| OTIS Mock AIME | 66.4% | Not measured | Only Qwen3 14B measured |
| ProofBench | Not measured | 70.0% | Only MiMo-V2.6-Pro 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 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Qwen3 14B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 45.0% | Only MiMo-V2.6-Pro measured |
| MMLU Pro (Artificial Analysis run) | 77.4% | Not measured | Only Qwen3 14B 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 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Qwen3 14B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1308 | Only MiMo-V2.6-Pro measured |
| Design Arena: UI components | Not measured | 1340 | Only MiMo-V2.6-Pro measured |
| Design Arena: game dev | Not measured | 1314 | Only MiMo-V2.6-Pro measured |
| Design Arena: data viz | Not measured | 1336 | Only MiMo-V2.6-Pro measured |
| Design Arena: 3D | Not measured | 1330 | Only MiMo-V2.6-Pro measured |
| Design Arena: all code categories | Not measured | 1317 | 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 | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3 14B | 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 |
| IFBench | 40.5% | Not measured | Only Qwen3 14B measured |
| Long context reasoning (AA-LCR) | 0.0% | 86.3% | MiMo-V2.6-Pro |
| DTBench | 64.0% | Not measured | Only Qwen3 14B measured |
| LMCA | 18.2% | Not measured | Only Qwen3 14B measured |
| Fiction.LiveBench | 62.5% | Not measured | Only Qwen3 14B 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 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3 14B | 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
Qwen3 14B costs less
Repository review
50K input + 3K output tokens
Qwen3 14B costs less
Agent loop
200K input + 10K output tokens
Qwen3 14B 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 | Qwen3 14B | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | Qwen | Xiaomi |
| Weights | Open weights | Open weights |
| Released | April 28, 2025 | September 21, 2026 |
| Context window | 41K | 1.05M |
| Input $/Mtok | $0.11 | $0.435 |
| Output $/Mtok | $0.23 | $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 Qwen3 14B better than MiMo-V2.6-Pro for coding?
Only MiMo-V2.6-Pro has a coding score, 65.4 on the Vibe Coding Index; Qwen3 14B has none, so the two cannot be ranked on coding. Pick Qwen3 14B for output tokens 3.8x cheaper ($0.23 vs $0.87 per million).
Which is cheaper, Qwen3 14B or MiMo-V2.6-Pro?
Qwen3 14B costs $0.11 per million input tokens and $0.23 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, Qwen3 14B or MiMo-V2.6-Pro?
MiMo-V2.6-Pro, with 1.05M tokens against 41K.
How many benchmarks is the Qwen3 14B vs MiMo-V2.6-Pro comparison based on?
4 benchmarks have a result for both models as of October 22, 2026. Qwen3 14B'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.