Model comparison
LFM2.5-8B-A1B vs Qwen3.6-35B-A3B
Head-to-head evidence from 13 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: LFM2.5-8B-A1B unranked; Qwen3.6-35B-A3B #31
BenchAlign evidence: LFM2.5-8B-A1B estimated; Qwen3.6-35B-A3B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. LFM2.5-8B-A1B and Qwen3.6-35B-A3B share 13 comparable benchmark results. 1 of 8 categories are comparable. 5 results are unique to LFM2.5-8B-A1B; 45 to Qwen3.6-35B-A3B.
Updated July 16, 2026- Shared results
- 13
- LFM2.5-8B-A1B only
- 5
- Qwen3.6-35B-A3B only
- 45
- Comparable categories
- 1 / 8
Pick Qwen3.6-35B-A3B if you want the stronger benchmark profile. LFM2.5-8B-A1B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.6-35B-A3B is clearly ahead on the provisional aggregate, 58 to 37. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-35B-A3B's sharpest advantage is in mathematics, where it averages 88.2 against 50. The single biggest benchmark swing on the page is AIME26, 50.0% to 92.7%.
Qwen3.6-35B-A3B gives you the larger context window at 262K, compared with 128K for LFM2.5-8B-A1B.
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 | LFM2.5-8B-A1B | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Math | LFM2.5-8B-A1B50.0 | Margin→ 38.2 | Qwen3.6-35B-A3B88.2 |
| Agentic | LFM2.5-8B-A1BNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.5 |
| Coding | LFM2.5-8B-A1BNot measured | MarginNo overlap | Qwen3.6-35B-A3B73.8 |
| Knowledge | LFM2.5-8B-A1BNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.8 |
| Multimodal | LFM2.5-8B-A1BNot measured | MarginNo overlap | Qwen3.6-35B-A3B76.3 |
| Inst. Following | LFM2.5-8B-A1B68.8 | MarginNo overlap | Qwen3.6-35B-A3BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
AIME26
MathA 50.0%B 92.7%Winner: Qwen3.6-35B-A3BΔ 42.7AIME26: LFM2.5-8B-A1B scored 50.0%; Qwen3.6-35B-A3B scored 92.7%. Qwen3.6-35B-A3B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | LFM2.5-8B-A1B | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | LFM2.5-8B-A1B$0 input / $0 output | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | LFM2.5-8B-A1BNot available | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | LFM2.5-8B-A1BNot available | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | LFM2.5-8B-A1B128K | Qwen3.6-35B-A3B262K | Qwen3.6-35B-A3B lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | LFM2.5-8B-A1B | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| BFCL v4Source | 49.7% | — | Not comparable |
| τ²-bench resultsSource | 16.1% | 95.3% | Qwen3.6-35B-A3B leads |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| Claw-EvalSource | — | 68.7% | Not comparable |
| QwenClawBenchSource | — | 52.6% | Not comparable |
| QwenWebBenchSource | — | 1397 | Not comparable |
| τ³-bench resultsSource | — | 67.2% | Not comparable |
| VITA-BenchSource | — | 35.6% | Not comparable |
| DeepPlanningSource | — | 25.9% | Not comparable |
| ToolathlonSource | — | 26.9% | Not comparable |
| MCP AtlasSource | — | 62.8% | Not comparable |
| WideResearchSource | — | 60.1% | Not comparable |
| AA Agentic IndexSource | — | 21.4% | Not comparable |
| GDPval-AASource | — | 27.4% | Not comparable |
| GDPval-AASource | — | 1049 | Not comparable |
| Gert LabsSource | — | 42.65% | Not comparable |
Coding9 benchmarks
| Benchmark | LFM2.5-8B-A1B | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Terminal-Bench HardSource | 4.5% | 34.8% | Qwen3.6-35B-A3B leads |
| AA-SciCodeSource | 7.8% | 35.8% | Qwen3.6-35B-A3B leads |
| SWE-bench VerifiedSource | — | 73.4% | Not comparable |
| SWE MultilingualSource | — | 67.2% | Not comparable |
| SWE-bench ProSource | — | 49.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| LiveCodeBenchSource | — | 80.4% | Not comparable |
| NL2RepoSource | — | 29.4% | Not comparable |
| AA Coding IndexSource | — | 41.9% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | LFM2.5-8B-A1B | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-GPQA DiamondSource | 51.3% | 84.1% | Qwen3.6-35B-A3B leads |
| AA-HLESource | 6.9% | 20.2% | Qwen3.6-35B-A3B leads |
| AA-Omniscience IndexSource | -33.3% | -21.4% | Qwen3.6-35B-A3B leads |
| AA-Omniscience AccuracySource | 9.4% | 18.9% | Qwen3.6-35B-A3B leads |
| AA-Omniscience Hallucination RateSource | 47.0% | 49.7% | LFM2.5-8B-A1B leads |
| Artificial Analysis Intelligence IndexSource | 8.3% | 31.6% | Qwen3.6-35B-A3B leads |
| MMLU-ProSource | — | 85.2% | Not comparable |
| SuperGPQASource | — | 64.7% | Not comparable |
| C-EvalSource | — | 90% | Not comparable |
| GPQASource | — | 86% | Not comparable |
| HLESource | — | 21.4% | Not comparable |
MathQwen3.6-35B-A3B wins7 benchmarks
| Benchmark | LFM2.5-8B-A1B | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| MATH-500Source | 88.8% | — | Not comparable |
| AIME 2025Source | 42.5% | — | Not comparable |
| AIME26Source | 50.0% | 92.7% | Qwen3.6-35B-A3B leads |
| HMMT Feb 2025Source | — | 90.7% | Not comparable |
| HMMT Nov 2025Source | — | 89.1% | Not comparable |
| HMMT Feb 2026Source | — | 83.6% | Not comparable |
| MMAnswerBenchSource | — | 78.9% | Not comparable |
Multimodal15 benchmarks
| Benchmark | LFM2.5-8B-A1B | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| MMMUSource | — | 81.7% | Not comparable |
| MMMU-ProSource | — | 75.3% | Not comparable |
| RealWorldQASource | — | 85.3% | Not comparable |
| OmniDocBench 1.5Source | — | 89.9% | Not comparable |
| CharXivSource | — | 78% | Not comparable |
| SimpleVQASource | — | 58.9% | Not comparable |
| CC-OCRSource | — | 81.9% | Not comparable |
| AI2D_TESTSource | — | 92.7% | Not comparable |
| RefCOCO (avg)Source | — | 92.0% | Not comparable |
| ODINW13Source | — | 50.8% | Not comparable |
| Video-MME (with subtitle)Source | — | 86.6% | Not comparable |
| Video-MME (w/o subtitle)Source | — | 82.5% | Not comparable |
| VideoMMMUSource | — | 83.7% | Not comparable |
| MLVU (M-Avg)Source | — | 86.2% | Not comparable |
| AA-MMMU-ProSource | — | 75.0% | Not comparable |
Frequently Asked Questions (2)
Which is better, LFM2.5-8B-A1B or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B is ahead on BenchLM's provisional leaderboard, 58 to 37. The biggest single separator in this matchup is AIME26, where the scores are 50.0% and 92.7%.
Which is better for math, LFM2.5-8B-A1B or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B has the edge for math in this comparison, averaging 88.2 versus 50. Inside this category, AIME26 is the benchmark that creates the most daylight between them.
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