Llama 3.3 Euryale 70B vs MiMo-V2.6-Pro
Llama 3.3 Euryale 70B and MiMo-V2.6-Pro cost about the same per output token ($0.75 vs $0.87 per million). Updated November 14, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.75
- Coding
- 61.8
- Overall
- 61.8
- Output $/M
- $0.87
Llama 3.3 Euryale 70B or MiMo-V2.6-Pro: which to pick
Only MiMo-V2.6-Pro has a coding score, 61.8 on the Vibe Coding Index; Llama 3.3 Euryale 70B has none, so the two cannot be ranked on coding.
Pick Llama 3.3 Euryale 70B for output tokens 1.2x cheaper ($0.75 vs $0.87 per million).
No benchmark has tested both yet. Llama 3.3 Euryale 70B has none yet; MiMo-V2.6-Pro on LiveBench coding, LMArena WebDev and Terminal-Bench 4 (Vals AI). 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
Only MiMo-V2.6-Pro has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only MiMo-V2.6-Pro has a AA Intelligence Index result, 29.9.
Directional only
Web design
Design Arena: websites
No call
Only MiMo-V2.6-Pro has a Design Arena: websites result, 1311.
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 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.6-Pro
Llama 3.3 Euryale 70B $0.0010, MiMo-V2.6-Pro $0.0009 per turn.
List prices
At a glance
- Coding index
- Llama 3.3 Euryale 70B not benchmarked, MiMo-V2.6-Pro 61.8 from 4 benchmarks.
- 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
- Llama 3.3 Euryale 70B $0.75 against MiMo-V2.6-Pro $0.87 per million output tokens, 1.2x apart.
- Context window
- Llama 3.3 Euryale 70B takes 131K tokens, MiMo-V2.6-Pro 1.05M.
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 Index21 boards measured
| Benchmark | Llama 3.3 Euryale 70B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 64.5% | 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 |
| SciCode | Not measured | 60.9% | Only MiMo-V2.6-Pro measured |
| Terminal-Bench 4.0 (Artificial Analysis run) | Not measured | 34.8% | Only MiMo-V2.6-Pro measured |
| FrontierCode 2.0 | Not measured | 24.0% | Only MiMo-V2.6-Pro measured |
| ALE-Bench | Not measured | 1158.1 | Only MiMo-V2.6-Pro measured |
| LMArena Text: coding | Not measured | 1534 | 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 | 1637 | Only MiMo-V2.6-Pro measured |
| LMArena WebDev: HTML | Not measured | 1622 | Only MiMo-V2.6-Pro measured |
| LMArena WebDev: from an image | Not measured | 1597 | Only MiMo-V2.6-Pro measured |
| GameBench 2 | Not measured | 70.9 | Only MiMo-V2.6-Pro measured |
| Terminal-Bench 4.0 | Not measured | 27.0% | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Llama 3.3 Euryale 70B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 29.9 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
| Benchmark | Llama 3.3 Euryale 70B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1270 | Only MiMo-V2.6-Pro measured |
| LiveBench research | Not measured | 84.8% | Only MiMo-V2.6-Pro measured |
| LiveBench browser | Not measured | 77.3% | Only MiMo-V2.6-Pro measured |
| LiveBench long agentic | Not measured | 36.4% | 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 32 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards measured
| Benchmark | Llama 3.3 Euryale 70B | 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 |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 49.4% | Only MiMo-V2.6-Pro measured |
| HLE-Diamond (Artificial Analysis run) | Not measured | 15.2% | Only MiMo-V2.6-Pro measured |
| CritPt v2, hard subset (Artificial Analysis run) | Not measured | 34.0% | Only MiMo-V2.6-Pro measured |
| LMArena Text: hard prompts | Not measured | 1511 | Only MiMo-V2.6-Pro measured |
| LMArena Text: expert | Not measured | 1539 | Only MiMo-V2.6-Pro measured |
| LMArena Text: hard prompts in English | Not measured | 1517 | Only MiMo-V2.6-Pro measured |
| LMArena Vision: diagrams | Not measured | 1283 | Only MiMo-V2.6-Pro measured |
| LMArena Vision: homework | Not measured | 1265 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Llama 3.3 Euryale 70B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| ProofBench | Not measured | 70.0% | Only MiMo-V2.6-Pro measured |
| LMArena Text: math | Not measured | 1495 | Only MiMo-V2.6-Pro measured |
| LMArena Text: mathematical work | Not measured | 1514 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Llama 3.3 Euryale 70B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 45.0% | Only MiMo-V2.6-Pro measured |
| AA-Omniscience | Not measured | -4.5 | Only MiMo-V2.6-Pro measured |
| LMArena Text: science | Not measured | 1504 | Only MiMo-V2.6-Pro measured |
| LMArena Text: medicine and healthcare | Not measured | 1492 | Only MiMo-V2.6-Pro measured |
| LMArena Text: legal and government | Not measured | 1486 | Only MiMo-V2.6-Pro measured |
| LMArena Text: business and finance | Not measured | 1466 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Llama 3.3 Euryale 70B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1311 | Only MiMo-V2.6-Pro measured |
| Design Arena: UI components | Not measured | 1333 | Only MiMo-V2.6-Pro measured |
| Design Arena: game dev | Not measured | 1312 | Only MiMo-V2.6-Pro measured |
| Design Arena: data viz | Not measured | 1336 | Only MiMo-V2.6-Pro measured |
| Design Arena: 3D | Not measured | 1319 | Only MiMo-V2.6-Pro measured |
| Design Arena: all code categories | Not measured | 1316 | Only MiMo-V2.6-Pro measured |
| Design Arena: SVG | Not measured | 1292 | Only MiMo-V2.6-Pro measured |
| LiveBench design | Not measured | 74.3% | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards measured
| Benchmark | Llama 3.3 Euryale 70B | 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 | 84.5% | 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 |
| GDPval-AA | Not measured | 1692 | Only MiMo-V2.6-Pro measured |
| LMArena Text | Not measured | 1492 | Only MiMo-V2.6-Pro measured |
| LMArena Text: instruction following | Not measured | 1492 | Only MiMo-V2.6-Pro measured |
| LMArena Text: creative writing | Not measured | 1468 | Only MiMo-V2.6-Pro measured |
| LMArena Vision | Not measured | 1266 | Only MiMo-V2.6-Pro measured |
| LMArena Text: English | Not measured | 1503 | Only MiMo-V2.6-Pro measured |
| LMArena Text: non-English | Not measured | 1475 | Only MiMo-V2.6-Pro measured |
| LMArena Text: Chinese | Not measured | 1528 | Only MiMo-V2.6-Pro measured |
| LMArena Text: Russian | Not measured | 1477 | Only MiMo-V2.6-Pro measured |
| LMArena Text: multi-turn | Not measured | 1471 | Only MiMo-V2.6-Pro measured |
| LMArena Text: longer queries | Not measured | 1503 | Only MiMo-V2.6-Pro measured |
| LMArena Text: writing and language | Not measured | 1469 | Only MiMo-V2.6-Pro measured |
| LMArena Text: entertainment and media | Not measured | 1463 | Only MiMo-V2.6-Pro measured |
| LMArena Vision: English | Not measured | 1270 | Only MiMo-V2.6-Pro measured |
| LMArena Vision: reading text | Not measured | 1274 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 28 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 | Sao10K Llama 3.3 Euryale 70B | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | Sao10K | Xiaomi |
| Weights | Open weights | Open weights |
| Released | December 18, 2024 | September 21, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.65 | $0.435 |
| Output $/Mtok | $0.75 | $0.87 |
| Coding index | Not benchmarked | 61.8 |
| Independent measurements behind it | 0 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 3.3 Euryale 70B better than MiMo-V2.6-Pro for coding?
Only MiMo-V2.6-Pro has a coding score, 61.8 on the Vibe Coding Index; Llama 3.3 Euryale 70B has none, so the two cannot be ranked on coding. Pick Llama 3.3 Euryale 70B for output tokens 1.2x cheaper ($0.75 vs $0.87 per million).
Which is cheaper, Llama 3.3 Euryale 70B or MiMo-V2.6-Pro?
Llama 3.3 Euryale 70B costs $0.65 per million input tokens and $0.75 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, Llama 3.3 Euryale 70B or MiMo-V2.6-Pro?
MiMo-V2.6-Pro, with 1.05M tokens against 131K.
Has any benchmark tested both Llama 3.3 Euryale 70B and MiMo-V2.6-Pro?
No benchmark has tested both yet. Llama 3.3 Euryale 70B has none yet; MiMo-V2.6-Pro on LiveBench coding, LMArena WebDev and Terminal-Bench 4 (Vals AI). Compare them on price and context instead. Data as of November 14, 2026.