Model comparison
Claude Opus 4.8 vs MiniMax M2.5
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: Claude Opus 4.8 #1; MiniMax M2.5 unranked
Evidence parity. Claude Opus 4.8 and MiniMax M2.5 share 0 comparable benchmark results. 0 of 8 categories are comparable. 53 results are unique to Claude Opus 4.8; 1 to MiniMax M2.5.
Updated July 14, 2026- Shared results
- 0
- Claude Opus 4.8 only
- 53
- MiniMax M2.5 only
- 1
- Comparable categories
- 0 / 8
Benchmark data for Claude Opus 4.8 and MiniMax M2.5 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Claude Opus 4.8 is priced at $5.00 input / $25.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.5. Claude Opus 4.8 has the larger context window at 1M, compared with 128K for MiniMax M2.5.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.8 | MiniMax M2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.8$5 input / $25 output | MiniMax M2.5$0.3 input / $1.2 output | MiniMax M2.5 has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.8Not available | MiniMax M2.546 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.8Not available | MiniMax M2.52.12 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.81M | MiniMax M2.5128K | Claude Opus 4.8 lists the larger context window. |
Benchmark Deep Dive
Agentic19 benchmarks
| Benchmark | Claude Opus 4.8 | MiniMax M2.5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 74.6% | — | Not comparable |
| BrowseCompSource | 84.3% | — | Not comparable |
| DeepSearchQASource | 93.1% | — | Not comparable |
| OSWorld-VerifiedSource | 83.4% | — | Not comparable |
| Finance Agent v2Source | 53.9% | — | Not comparable |
| GDPval-AASource | 1600 | — | Not comparable |
| MCP AtlasSource | 82.2% | — | Not comparable |
| ToolathlonSource | 59.9% | — | Not comparable |
| Gert LabsSource | 72.97% | — | Not comparable |
| AA Agentic IndexSource | 47.2% | — | Not comparable |
| Tau2-TelecomSource | 94.4% | — | Not comparable |
| GDPval-AASource | 55.0% | — | Not comparable |
| ResearchClawBenchSource | 21.1% | — | Not comparable |
| OSWorld 2.0Source | 20.6% | — | Not comparable |
| AA BriefcaseSource | 1354 | — | Not comparable |
| AA AutomationBenchSource | 48.5% | — | Not comparable |
| AA EnterpriseOps-GymSource | 44.0% | — | Not comparable |
| AA Harvey LABSource | 7.5% | — | Not comparable |
| AA Tau3 BankingSource | 27.6% | — | Not comparable |
Coding13 benchmarks
| Benchmark | Claude Opus 4.8 | MiniMax M2.5 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 88.6% | — | Not comparable |
| SWE-bench ProSource | 69.2% | — | Not comparable |
| SWE MultilingualSource | 84.4% | — | Not comparable |
| SWE MultimodalSource | 38.4% | — | Not comparable |
| Terminal-Bench 2.0Source | 74.6% | — | Not comparable |
| cursorBench31Source | 58.4% | — | Not comparable |
| cursorBench32Source | 62.3% | — | Not comparable |
| AA Coding IndexSource | 74.3% | — | Not comparable |
| Terminal-Bench HardSource | 58.3% | — | Not comparable |
| AA-SciCodeSource | 53.5% | — | Not comparable |
| FrontierCodeSource | 46.5% | — | Not comparable |
| AA Terminal-Bench 2.1Source | 84.6% | — | Not comparable |
| Vibe Code BenchSource | — | 14.85% | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | Claude Opus 4.8 | MiniMax M2.5 | Result |
|---|---|---|---|
| GPQASource | 93.6% | — | Not comparable |
| GPQA-DSource | 93.6% | — | Not comparable |
| HLESource | 57.9% | — | Not comparable |
| HLE w/o toolsSource | 49.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 55.7% | — | Not comparable |
| AA-GPQA DiamondSource | 92.0% | — | Not comparable |
| AA-HLESource | 45.7% | — | Not comparable |
| AA-Omniscience IndexSource | 27.4% | — | Not comparable |
| AA-Omniscience AccuracySource | 46.6% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 35.9% | — | Not comparable |
Math3 benchmarks
Multilingual1 benchmarks
| Benchmark | Claude Opus 4.8 | MiniMax M2.5 | Result |
|---|---|---|---|
| INCLUDESource | 87.6% | — | Not comparable |
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.8 | MiniMax M2.5 | Result |
|---|---|---|---|
| AA-IFBenchSource | 62.2% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Claude Opus 4.8 and MiniMax M2.5 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Claude Opus 4.8 and MiniMax M2.5 today?
Claude Opus 4.8: $5.00 input / $25.00 output per 1M tokens MiniMax M2.5: $0.30 input / $1.20 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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