Model comparison
Claude Opus 4.6 vs LFM2-24B-A2B
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: Claude Opus 4.6 #20 (Supported); LFM2-24B-A2B #207 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.6 and LFM2-24B-A2B share 0 comparable benchmark results. 0 of 8 categories are comparable. 46 results are unique to Claude Opus 4.6; 0 to LFM2-24B-A2B.
Updated July 28, 2026- Shared results
- 0
- Claude Opus 4.6 only
- 46
- LFM2-24B-A2B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Claude Opus 4.6 and LFM2-24B-A2B 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 does not have sourced benchmark coverage for LFM2-24B-A2B yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Claude Opus 4.6 is priced at $5.00 input / $25.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2-24B-A2B. Claude Opus 4.6 has the larger context window at 1M, compared with 32K for LFM2-24B-A2B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.6 | LFM2-24B-A2B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.6$5 input / $25 output | LFM2-24B-A2B$0 input / $0 output | LFM2-24B-A2B has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.640 tok/s | LFM2-24B-A2B92 tok/s | LFM2-24B-A2B has the higher measured throughput. |
| First-answer latencyseconds to first token | Claude Opus 4.61.78 s | LFM2-24B-A2B0.42 s | LFM2-24B-A2B reaches the first token sooner. |
| Context windowmaximum listed tokens | Claude Opus 4.61M | LFM2-24B-A2B32K | Claude Opus 4.6 lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | Claude Opus 4.6 | LFM2-24B-A2B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 65.4% | — | Not comparable |
| BrowseCompSource | 83.7% | — | Not comparable |
| OSWorld-VerifiedSource | 72.7% | — | Not comparable |
| τ²-bench resultsSource | 84.8% | — | Not comparable |
| Claw-EvalSource | 70.4% | — | Not comparable |
| DeepSearchQASource | 73.7% | — | Not comparable |
| CyberGymSource | 66.6% | — | Not comparable |
| Gert LabsSource | 61.85% | — | Not comparable |
| ResearchClawBenchSource | 19.9% | — | Not comparable |
| JobBenchSource | 36.7% | — | Not comparable |
Coding9 benchmarks
| Benchmark | Claude Opus 4.6 | LFM2-24B-A2B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.8% | — | Not comparable |
| SWE-bench Verified*Source | 75.6% | — | Not comparable |
| LiveCodeBench ProSource | 70.7% | — | Not comparable |
| SWE-bench ProSource | 53.4% | — | Not comparable |
| SWE-RebenchSource | 65.3% | — | Not comparable |
| React Native EvalsSource | 84.1% | — | Not comparable |
| Vibe Code BenchSource | 57.57% | — | Not comparable |
| AA-SciCodeSource | 45.7% | — | Not comparable |
| FrontierCode 1.1 MainSource | 26.9% | — | Not comparable |
Reasoning2 benchmarks
Knowledge15 benchmarks
| Benchmark | Claude Opus 4.6 | LFM2-24B-A2B | Result |
|---|---|---|---|
| GPQASource | 91.3% | — | Not comparable |
| GPQA-DSource | 89.2% | — | Not comparable |
| SuperGPQASource | 95% | — | Not comparable |
| MMLU-ProSource | 82% | — | Not comparable |
| MMLU-Pro (Arcee)Source | 89.1% | — | Not comparable |
| HLESource | 53% | — | Not comparable |
| HLE w/o toolsSource | 40% | — | Not comparable |
| HealthBench HardSource | 14.8% | — | Not comparable |
| MedXpertQA (Text)Source | 52.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 37.8% | — | Not comparable |
| AA-GPQA DiamondSource | 84.0% | — | Not comparable |
| AA-HLESource | 18.6% | — | Not comparable |
| AA-Omniscience IndexSource | 3.5% | — | Not comparable |
| AA-Omniscience AccuracySource | 45.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 76.0% | — | Not comparable |
Math3 benchmarks
Multimodal6 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.6 | LFM2-24B-A2B | Result |
|---|---|---|---|
| AA-IFBenchSource | 44.6% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Claude Opus 4.6 and LFM2-24B-A2B 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 4.6 and LFM2-24B-A2B today?
Claude Opus 4.6: $5.00 input / $25.00 output per 1M tokens LFM2-24B-A2B: $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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