Claude Opus 5 vs Mimo v2 Omni
Full profiles: Claude Opus 5 (Anthropic) and Mimo v2 Omni (Xiaomi): every benchmark, price and rank.
Updated · Data from 11 sources
As of 29 Oct 2026, Claude Opus 5 is ahead of Mimo v2 Omni on quality (65.5 vs 58.9 on the BenchLeader Index). Claude Opus 5 leads in every category we measure both in.
Key facts (as of 29 Oct 2026)
- Claude Opus 5 scores 65.5 on the BenchLeader Index and Mimo v2 Omni scores 58.9 (BenchLeader, 29 Oct 2026).
- Claude Opus 5 costs $10.00 per 1M tokens blended (list price, 29 Oct 2026).
- Of the 13 benchmarks both models have, Claude Opus 5 leads 13 (BenchLeader, 29 Oct 2026).
Which to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | Claude Opus 5 | 70 vs 62 category score; Arena Coding 1528 vs 1488 | High |
| Agents & tool use | Either | 64 vs 65 category score | Either |
| Maths | Claude Opus 5 | 70 vs 61 category score; Arena Maths 1517 vs 1434 | High |
| Reasoning | Claude Opus 5 | 69 vs 62 category score; Arena Hard Prompts 1515 vs 1458 | Medium |
| Long documents | Claude Opus 5 | 65 vs 61 category score; AA-LCR v1.1 79.3% vs 73.3% | Medium |
| Images and other media | Claude Opus 5 | 68 vs 56 category score; MMMU-Pro 84.7% vs 73.9% | High |
| Chat quality (human preference) | Claude Opus 5 | 68 vs 61 on Arena votes | Medium |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- Claude Opus 5 (max) leads on quality: 65.5 vs 58.9.
- Claude Opus 5 (max) is stronger in coding, human preference, knowledge, long context, maths, multimodal, reasoning.
- Mimo v2 Omni is stronger in agents & tools, instruction following.
At a glance
| Spec | Claude Opus 5 | Mimo v2 Omni |
|---|---|---|
| Developer | Anthropic | Xiaomi |
| Released | 24 Jul 2026 | 27 Mar 2026 |
| Context window (tokens) | 1,000,000 | 256,000 |
| Compared at | Claude Opus 5 (max) | Mimo v2 Omni |
| Open weights | No | No |
| Price in / out / cached input per 1M | $5.00 / $25.00 / $0.500 | – |
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | Claude Opus 5 (max) | Mimo v2 Omni | Leader |
|---|---|---|---|
| Reasoning | 69.2 | 61.9 | Claude Opus 5 |
| Coding | 70.0 | 62.1 | Claude Opus 5 |
| Agents & tools | 64.3 | 64.8 | level |
| Maths | 70.4 | 61.0 | Claude Opus 5 |
| Knowledge | 65.0 | – | not comparable |
| Instruction following | – | 66.5 | not comparable |
| Human preference | 68.4 | 61.1 | Claude Opus 5 |
| Multimodal | 67.6 | 55.9 | Claude Opus 5 |
| Long context | 64.5 | 61.4 | Claude Opus 5 |
Where sources disagree
Across the 13 benchmarks both have, Claude Opus 5 leads 13, Mimo v2 Omni leads 0. Every overall index that rates both puts Claude Opus 5 ahead.
| Overall index | Claude Opus 5 (max) | Mimo v2 Omni | Leader |
|---|---|---|---|
| BenchLeader Index | 65.5 | 58.9 | Claude Opus 5 |
| Arena Text | 1491 | 1431 | Claude Opus 5 |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | Claude Opus 5 (max) | Mimo v2 Omni |
|---|---|---|
| Blended price per 1M tokens | $10.00 | – |
| Input / output per 1M | $5.00 / $25.00 | – / – |
| Cached input per 1M | $0.500 | – |
| Price per task: chat reply | $0.0095 | – |
| Price per task: summarize a 30-page report | $0.075 | – |
| Price per task: code edit | $0.068 | – |
| Price per task: agentic coding session | $0.400 | – |
| Price per task: structured extraction | $0.015 | – |
| Output speed | 56 tok/s | – |
| Time to first answer | 43.9 s | – |
| Time to a complete answer | 52.8 s | – |
Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 5 (max) scores 65.5 and takes 44 s to its first answer token; Claude Opus 5 scores 65.2 in 3 s, Claude Opus 5 (high) scores 64.4 in 14 s. Mimo v2 Omni scores 58.9. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
121 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | Claude Opus 5 (max) | Mimo v2 Omni |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 65.5 | 58.9 |
| Agents & tools score | BenchLeader | 64.3 | 64.8 |
| Coding score | BenchLeader | 70.0 | 62.1 |
| Human preference score | BenchLeader | 68.4 | 61.1 |
| Knowledge score | BenchLeader | 65.0 | – |
| Long context score | BenchLeader | 64.5 | 61.4 |
| Maths score | BenchLeader | 70.4 | 61.0 |
| Multimodal score | BenchLeader | 67.6 | 55.9 |
| Reasoning score | BenchLeader | 69.2 | 61.9 |
| Instruction following score | BenchLeader | – | 66.5 |
| Blended price $/M | BenchLeader | $10.00 | – |
| Output speed | BenchLeader | 56 tok/s | – |
| Time to first answer | BenchLeader | 43.9 s | – |
| Context window | BenchLeader | 1,000,000 tokens | 256,000 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 93.9% | – |
| SimpleBench | SimpleBench | 80.6%† | – |
| Arena Hard Prompts | Arena (LMArena) | 1515 | 1458 |
| LiveBench 1.0 Reasoning | LiveBench | 91.2% | – |
| GPQA Diamond (AA) | Artificial Analysis | 93.2% | 85.5% |
| Humanity's Last Exam (AA) | Artificial Analysis | 54.9% | 22.6% |
| GPQA Diamond (Vals) | Vals AI | 93.4%† | – |
| ARC-AGI-1 | ARC Prize | 97.5% | – |
| ARC-AGI-2 | ARC Prize | 90.4% | – |
| ARC-AGI-3 | ARC Prize | 30.2%† | – |
| CritPt | Artificial Analysis | 29.1% | 0.9% |
| MysteryMechanism | Vals AI | 37.4%† | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | 43.0% | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 59.0% | – |
| LMCA | Epoch AI Benchmarking Hub | 63.3% | – |
| DTBench | Epoch AI Benchmarking Hub | 97.6% | – |
| ForecastBench | ForecastBench | 66.5% | – |
| BTF-3 | Epoch AI Benchmarking Hub | 12.0%† | – |
| Coding | |||
| SciCode | SciCode | 56.4% | – |
| WeirdML | WeirdML | 91.8% | – |
| FrontierCode | Cognition | 53.4% | – |
| Arena Coding | Arena (LMArena) | 1528 | 1488 |
| Arena WebDev | Arena (LMArena) | 1690 | – |
| LiveBench 1.0 Coding | LiveBench | 81.5% | – |
| LiveCodeBench | Vals AI | 89.0%† | – |
Show all 121 benchmarks
| Metric | Publisher | Claude Opus 5 (max) | Mimo v2 Omni |
|---|---|---|---|
| Coding | |||
| IOI | Vals AI | 84.3%† | – |
| SWE-bench (Vals) | Vals AI | 97.0%† | – |
| Code Migration | Vals AI | 57.5%† | – |
| ProgramBench | Vals AI | 3.0%† | – |
| Vibe Code Bench 1-100 | Vals AI | 28.5%† | – |
| Vibe Code Bench v1.1 | Vals AI | 88.4%† | – |
| SWE Atlas: Codebase QnA | Scale AI SEAL | 63.2%† | – |
| SWE Atlas: Test Writing | Scale AI SEAL | 62.2%† | – |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 73.7% | – |
| CursorBench | Cursor | 46.6% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 2164.6† | – |
| FrontierSWE | Epoch AI Benchmarking Hub | 52.0% | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 49.0% | – |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 89.1% | – |
| Startrise Frontend | Startrise | 82.3%† | – |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 51.8% | – |
| OSWorld-Verified 2.0 | OSWorld | 31.4% | – |
| APEX-Agents | Mercor | 65.8% | – |
| Arena Agent | Arena (LMArena) | 8.2 | – |
| LiveBench Agentic Coding | LiveBench | 65.2% | – |
| Terminal-Bench Hard | Artificial Analysis | – | 35.6% |
| τ²-Bench Telecom (AA) | Artificial Analysis | – | 88.0% |
| Terminal-Bench 2.1 (Vals) | Vals AI | 84.6%† | – |
| MCP Atlas | Scale AI SEAL | 85.8%† | – |
| HiL-Bench | Scale AI SEAL | 57.0%† | – |
| τ³-bench Banking | τ²-bench | 48.7% | – |
| τ³-Banking (AA) | Artificial Analysis | 42.1% | – |
| Analyst Agent (AA) | Artificial Analysis | 53.8% | – |
| CUA-bench | Vals AI | 9.0% | – |
| CyberBench | Vals AI | 65.4%† | – |
| Finance Agent v2 | Vals AI | 58.6%† | – |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 6.7%† | – |
| Legal Research Bench | Vals AI | 55.3%† | – |
| SkillsBench | Vals AI | 60.4%† | – |
| SREBench | Vals AI | 12.2%† | – |
| Tax Agent Bench | Vals AI | 45.5%† | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | 53.5%† | – |
| Terminal-Bench Science | Vals AI | 27.1%† | – |
| Time Horizon Index: KSP | Vals AI | 18.8%† | – |
| Arena Search | Arena (LMArena) | 1214† | – |
| BALROG | BALROG | 63.4% | – |
| PostTrainBench | Epoch AI Benchmarking Hub | 35.0%† | – |
| GBAEval | Epoch AI Benchmarking Hub | 79.6%† | – |
| Vending-Bench 2 | Andon Labs | 11181.9† | – |
| AutomationBench | Artificial Analysis | 56.6% | – |
| GDP.pdf (AA) | Artificial Analysis | 21.6% | – |
| EnterpriseOps-Gym | Artificial Analysis | 47.5% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1655 | – |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 28.6% | – |
| DeepSec-Bench (AA) | Artificial Analysis | 25.9% | – |
| FACTS Search | 85.3%† | – | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 85.6% | – |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 73.2% | – |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 98.9% | – |
| ProofBench | Vals AI | 99.0% | – |
| LiveBench Mathematics | LiveBench | 95.7% | – |
| Arena Maths | Arena (LMArena) | 1517 | 1434 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 59.9% | – |
| LiveBench 1.0 Data Analysis | LiveBench | 74.5% | – |
| MMLU-Pro | Vals AI | 91.6%† | – |
| LegalBench | Vals AI | 87.0%† | – |
| CorpFin | Vals AI | 73.2%† | – |
| TaxEval | Vals AI | 75.1%† | – |
| BioMysteryBench | Vals AI | 79.3%† | – |
| Excel Modeling Benchmark | Vals AI | 73.6%† | – |
| MedCode | Vals AI | 63.6%† | – |
| MedScribe | Vals AI | 91.0%† | – |
| Public Benefits Bench v1.1 | Vals AI | 76.9%† | – |
| DrugDiscoveryBench | Scale AI SEAL | 53.7% | – |
| EBR-bench | Epoch AI Benchmarking Hub | 45.7% | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 24.0% | – |
| Instruction following | |||
| LiveBench Language | LiveBench | 88.7% | – |
| LiveBench Instruction Following | LiveBench | 63.8% | – |
| IFBench | Artificial Analysis | – | 67.3% |
| Arena Instruction Following | Arena (LMArena) | 1495 | 1428 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1491 | 1431 |
| EQ-Bench 4 | EQ-Bench | 1365† | – |
| Arena Creative Writing | Arena (LMArena) | 1474 | 1395 |
| Arena Multi-turn | Arena (LMArena) | 1487 | 1452 |
| Arena Longer Queries | Arena (LMArena) | 1503 | 1450 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1320† | 1228 |
| MMMU-Pro | Artificial Analysis | 84.7% | 73.9% |
| MMMU-Pro (Vals) | Vals AI | 89.9%† | – |
| MortgageTax | Vals AI | 72.1%† | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 30.4%† | – |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 79.3% | 73.3% |
| Arena Document | Arena (LMArena) | 1490† | – |
| MLCR | Artificial Analysis | 11.1% | – |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 163.9† | – |
| LiveBench 1.0 | LiveBench | 80.1% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 50.8 | 25.1 |
| AA Progress Index v1 | Artificial Analysis | 333.7 | 269 |
| Vals RSI Index | Vals AI | 33.0% | – |
| Vals Science Index | Vals AI | 47.9%† | – |
| Vals Multimodal Index | Vals AI | 73.9%† | – |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 16.8%† | – |
Data as of 2026-10-29. Best configuration of each model; every score links to its source on the model pages.
What changed
- Claude Opus 5 (max): BenchLeader Index 66.3 → 65.5.
- Claude Opus 5 (max): 1 new result (AA Progress Index v1).
- Mimo v2 Omni: 1 new result (AA Progress Index v1).
- Claude Opus 5 (max): BenchLeader Index 66.8 → 66.3.
- Claude Opus 5 (max): 1 new result (Vals RSI Index).
- Claude Opus 5 (max): 1 score revision.
- Claude Opus 5 (max): 1 new result (ForecastBench); 1 score revision.
- Mimo v2 Omni: BenchLeader Index 57.5 → 58.7.
- Claude Opus 5 (max): 4 new results (GDPval-AA v2.1, normalised score, AA-Omniscience v1.1: accuracy, AA-Omniscience v1.1: non-hallucination…).
- Mimo v2 Omni: 7 score revisions.
Related comparisons
- Claude Opus 5 vs Claude Opus 5.5
- Claude Opus 5 vs GPT-6 Astra
- Claude Opus 5 vs GPT-6.1 Sol
- Mimo v2 Omni vs Claude Opus 5.5
- Mimo v2 Omni vs GPT-6 Astra
- Mimo v2 Omni vs GPT-6.1 Sol
- Mimo v2 Omni vs Claude Fable 5.1
- Claude Fable 5 vs Mimo v2 Omni
Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
Claude Opus 5 vs Mimo v2 Omni: questions
- Is Claude Opus 5 better than Mimo v2 Omni?
- Claude Opus 5 (max) leads on quality: 65.5 vs 58.9. The BenchLeader Index combines every independent quality benchmark; Claude Opus 5 (max) is ahead overall as of 29 Oct 2026, but check the category scores for your use.
- Is Claude Opus 5 or Mimo v2 Omni better for coding?
- Claude Opus 5 scores higher in coding (70 vs 62 on the category index, where 50 is average). On Arena Coding, the top shared coding benchmark, it is 1528 for Claude Opus 5 against 1488 for Mimo v2 Omni.
- Is Claude Opus 5 or Mimo v2 Omni better for agents and tool use?
- They are level in agentic tasks (64 vs 65 on the category index).
- Which is better for long documents?
- Claude Opus 5 scores higher on long-context benchmarks (65 vs 61). Claude Opus 5 accepts more context: 1,000,000 against 256,000 tokens for Mimo v2 Omni.
- Do independent benchmarks agree on Claude Opus 5 vs Mimo v2 Omni?
- Across the 13 benchmarks both have, Claude Opus 5 leads 13, Mimo v2 Omni leads 0. Every overall index that rates both puts Claude Opus 5 ahead.
More questions (1)
- When was Claude Opus 5 released?
- Claude Opus 5 was released on 24 Jul 2026.