Model comparison
GPT-5.5 vs MiMo-V2.5
Head-to-head evidence from 7 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.5 #9 (Estimated); MiMo-V2.5 #62 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.5 and MiMo-V2.5 share 7 comparable benchmark results. 3 of 8 categories are comparable. 50 results are unique to GPT-5.5; 4 to MiMo-V2.5.
Updated July 22, 2026- Shared results
- 7
- GPT-5.5 only
- 50
- MiMo-V2.5 only
- 4
- Comparable categories
- 3 / 8
Pick GPT-5.5 if you want the stronger benchmark profile. MiMo-V2.5 only becomes the better choice if multimodal & grounded is the priority.
Confidence note. This is a partial-evidence comparison with 7 shared benchmark results across 3 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.5 is clearly ahead on the BenchAlign aggregate, 73.51 to 58.62. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.5's sharpest advantage is in agentic, where it averages 81.6 against 65.8. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 82% to 65.8%. MiMo-V2.5 does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-5.5 | Δ | MiMo-V2.5 |
|---|---|---|---|
| Agentic | GPT-5.581.6 | Margin← 15.8 | MiMo-V2.565.8 |
| Multimodal | GPT-5.570.4 | Margin→ 8.6 | MiMo-V2.579.0 |
| Coding | GPT-5.558.6 | Margin← 2.5 | MiMo-V2.556.1 |
| Reasoning | GPT-5.585.0 | MarginNo overlap | MiMo-V2.5Not measured |
| Knowledge | GPT-5.557.8 | MarginNo overlap | MiMo-V2.5Not measured |
| Math | GPT-5.547.6 | MarginNo overlap | MiMo-V2.5Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 82%B 65.8%Winner: GPT-5.5Δ 16.2Terminal-Bench 2.0: GPT-5.5 scored 82%; MiMo-V2.5 scored 65.8%. GPT-5.5 wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 81.2%B 77.9%Winner: GPT-5.5Δ 3.3MMMU-Pro: GPT-5.5 scored 81.2%; MiMo-V2.5 scored 77.9%. GPT-5.5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 58.6%B 56.1%Winner: GPT-5.5Δ 2.5SWE-bench Pro: GPT-5.5 scored 58.6%; MiMo-V2.5 scored 56.1%. GPT-5.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.5 | MiMo-V2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.5$5 input / $30 output | MiMo-V2.5Not available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.5Not available | MiMo-V2.5Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.5Not available | MiMo-V2.5Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.51M | MiMo-V2.51M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGPT-5.5 wins26 benchmarks
| Benchmark | GPT-5.5 | MiMo-V2.5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 82% | 65.8% | GPT-5.5 leads |
| CyberGymSource | 81.8% | — | Not comparable |
| BrowseCompSource | 84.4% | — | Not comparable |
| OSWorld-VerifiedSource | 78.7% | — | Not comparable |
| MCP AtlasSource | 75.3% | — | Not comparable |
| ToolathlonSource | 55.6% | — | Not comparable |
| τ²-bench resultsSource | 93.9% | — | Not comparable |
| AA Agentic IndexSource | 44.9% | — | Not comparable |
| APEX-Agents-AASource | 37.7% | — | Not comparable |
| GDPval-AASource | 49.5% | — | Not comparable |
| GDPval-AASource | 1490 | — | Not comparable |
| Gert LabsSource | 72.93% | 46.89% | GPT-5.5 leads |
| ResearchClawBenchSource | 17.0% | 16.9% | GPT-5.5 leads |
| OSWorld 2.0Source | 13.0% | — | Not comparable |
| JobBenchSource | 42.7% | — | Not comparable |
| ExploitGymSource | 13.4% | — | Not comparable |
| AA BriefcaseSource | 1154 | — | Not comparable |
| AA AutomationBenchSource | 42.1% | — | Not comparable |
| AA EnterpriseOps-GymSource | 46.6% | — | Not comparable |
| AA Harvey LABSource | 86.3% | — | Not comparable |
| AA ITBenchSource | 45.8% | — | Not comparable |
| AA Tau3 BankingSource | 31.3% | — | Not comparable |
| terminalBenchHardSource | 60.6% | — | Not comparable |
| aaTerminalBench21Source | 84.3% | — | Not comparable |
| Claw-EvalSource | — | 62.3% | Not comparable |
| MM-ClawBenchSource | — | 23.8% | Not comparable |
CodingGPT-5.5 wins9 benchmarks
| Benchmark | GPT-5.5 | MiMo-V2.5 | Result |
|---|---|---|---|
| SWE-bench ProSource | 58.6% | 56.1% | GPT-5.5 leads |
| Terminal-Bench 2.0Source | 82.0% | 65.8% | GPT-5.5 leads |
| Vibe Code BenchSource | 69.85% | — | Not comparable |
| React Native EvalsSource | 84.7% | — | Not comparable |
| cursorBench31Source | 59.2% | — | Not comparable |
| cursorBench32Source | 58.4% | — | Not comparable |
| AA Coding IndexSource | 74.9% | — | Not comparable |
| AA-SciCodeSource | 56.1% | — | Not comparable |
| FrontierCode 1.1 MainSource | 43.0% | — | Not comparable |
Reasoning5 benchmarks
Knowledge10 benchmarks
| Benchmark | GPT-5.5 | MiMo-V2.5 | Result |
|---|---|---|---|
| GPQASource | 93.6% | — | Not comparable |
| GPQA-DSource | 93.6% | — | Not comparable |
| HLESource | 52.2% | — | Not comparable |
| HLE w/o toolsSource | 41.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 54.8% | — | Not comparable |
| AA-GPQA DiamondSource | 93.5% | — | Not comparable |
| AA-HLESource | 44.3% | — | Not comparable |
| AA-Omniscience IndexSource | 20.1% | — | Not comparable |
| AA-Omniscience AccuracySource | 56.9% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 85.5% | — | Not comparable |
Math3 benchmarks
MultimodalMiMo-V2.5 wins7 benchmarks
| Benchmark | GPT-5.5 | MiMo-V2.5 | Result |
|---|---|---|---|
| MMMU-ProSource | 81.2% | 77.9% | GPT-5.5 leads |
| MMMU-Pro w/ PythonSource | 83.2% | — | Not comparable |
| OfficeQA ProSource | 54.1% | — | Not comparable |
| AA-MMMU-ProSource | 79.9% | — | Not comparable |
| Design Arena WebsiteSource | 1282 | 1291 | MiMo-V2.5 leads |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| CharXivSource | — | 81% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.5 | MiMo-V2.5 | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.9% | — | Not comparable |
Frequently Asked Questions (4)
Which is better, GPT-5.5 or MiMo-V2.5?
GPT-5.5 is ahead on BenchLM's BenchAlign leaderboard, 73.51 to 58.62. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 82% and 65.8%.
Which is better for coding, GPT-5.5 or MiMo-V2.5?
GPT-5.5 has the edge for coding in this comparison, averaging 58.6 versus 56.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.5 or MiMo-V2.5?
GPT-5.5 has the edge for agentic tasks in this comparison, averaging 81.6 versus 65.8. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.5 or MiMo-V2.5?
MiMo-V2.5 has the edge for multimodal and grounded tasks in this comparison, averaging 79 versus 70.4. Inside this category, Design Arena Website is the benchmark that creates the most daylight between them.
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