Model comparison
GPT-OSS 120B vs LFM2.5-230M
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 120B #116 (Supported); LFM2.5-230M unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-OSS 120B and LFM2.5-230M share 0 comparable benchmark results. 0 of 8 categories are comparable. 26 results are unique to GPT-OSS 120B; 6 to LFM2.5-230M.
Updated July 23, 2026- Shared results
- 0
- GPT-OSS 120B only
- 26
- LFM2.5-230M only
- 6
- Comparable categories
- 0 / 8
Benchmark data for GPT-OSS 120B and LFM2.5-230M 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.
GPT-OSS 120B has the larger context window at 128K, compared with 32K for LFM2.5-230M.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-OSS 120B | LFM2.5-230M | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-OSS 120B$0 input / $0 output | LFM2.5-230M$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | GPT-OSS 120B262 tok/s | LFM2.5-230MNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-OSS 120B0.79 s | LFM2.5-230MNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-OSS 120B128K | LFM2.5-230M32K | GPT-OSS 120B lists the larger context window. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | GPT-OSS 120B | LFM2.5-230M | Result |
|---|---|---|---|
| AA Agentic IndexSource | 13.2% | — | Not comparable |
| APEX-Agents-AASource | 3.1% | — | Not comparable |
| τ²-bench resultsSource | 65.8% | — | Not comparable |
| GDPval-AASource | 15.0% | — | Not comparable |
| GDPval-AASource | 799 | — | Not comparable |
| Gert LabsSource | 29.61% | — | Not comparable |
| AA EnterpriseOps-GymSource | 25.5% | — | Not comparable |
| AA ITBenchSource | 5.6% | — | Not comparable |
| BFCL v4Source | — | 21.0% | Not comparable |
Coding4 benchmarks
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | GPT-OSS 120B | LFM2.5-230M | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 23.8% | — | Not comparable |
| AA-GPQA DiamondSource | 78.2% | — | Not comparable |
| AA-HLESource | 18.5% | — | Not comparable |
| AA-Omniscience IndexSource | -50.0% | — | Not comparable |
| AA-Omniscience AccuracySource | 21.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 91.2% | — | Not comparable |
| AA Openness IndexSource | 38.9% | — | Not comparable |
| AA MMLU-ProSource | 80.8% | — | Not comparable |
| GPQASource | — | 25.4% | Not comparable |
| GPQA-DSource | — | 25.4% | Not comparable |
| MMLU-ProSource | — | 20.3% | Not comparable |
Math1 benchmarks
| Benchmark | GPT-OSS 120B | LFM2.5-230M | Result |
|---|---|---|---|
| AA AIME 2025Source | 93.4% | — | Not comparable |
Multilingual1 benchmarks
| Benchmark | GPT-OSS 120B | LFM2.5-230M | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | 82.8% | — | Not comparable |
Multimodal1 benchmarks
| Benchmark | GPT-OSS 120B | LFM2.5-230M | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 998 | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-OSS 120B and LFM2.5-230M 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 120B and LFM2.5-230M today?
GPT-OSS 120B: $0.00 input / $0.00 output per 1M tokens LFM2.5-230M: $0.00 input / $0.00 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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