Model comparison
GPT-OSS 20B vs MiniMax M2.5
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-OSS 20B #159 (Supported); MiniMax M2.5 #55 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-OSS 20B and MiniMax M2.5 share 0 comparable benchmark results. 0 of 8 categories are comparable. 18 results are unique to GPT-OSS 20B; 1 to MiniMax M2.5.
Updated July 22, 2026- Shared results
- 0
- GPT-OSS 20B only
- 18
- MiniMax M2.5 only
- 1
- Comparable categories
- 0 / 8
Benchmark data for GPT-OSS 20B 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.
MiniMax M2.5 is priced at $0.30 input / $1.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GPT-OSS 20B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-OSS 20B | MiniMax M2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-OSS 20B$0 input / $0 output | MiniMax M2.5$0.3 input / $1.2 output | GPT-OSS 20B has the lower combined listed price. |
| Generation speedtokens per second | GPT-OSS 20B313 tok/s | MiniMax M2.546 tok/s | GPT-OSS 20B has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-OSS 20B0.65 s | MiniMax M2.52.12 s | GPT-OSS 20B reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-OSS 20B128K | MiniMax M2.5128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding4 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GPT-OSS 20B | MiniMax M2.5 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 14.9% | — | Not comparable |
| AA-GPQA DiamondSource | 68.8% | — | Not comparable |
| AA-HLESource | 9.8% | — | Not comparable |
| AA-Omniscience IndexSource | -63.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 15.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 94.1% | — | Not comparable |
Multimodal1 benchmarks
| Benchmark | GPT-OSS 20B | MiniMax M2.5 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 882 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-OSS 20B | MiniMax M2.5 | Result |
|---|---|---|---|
| AA-IFBenchSource | 65.1% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-OSS 20B 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 GPT-OSS 20B and MiniMax M2.5 today?
GPT-OSS 20B: $0.00 input / $0.00 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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