Model comparison
LFM2.5-VL-1.6B-Extract vs Qwen3.6-35B-A3B
Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: LFM2.5-VL-1.6B-Extract unranked (Not scored); Qwen3.6-35B-A3B #104 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. LFM2.5-VL-1.6B-Extract and Qwen3.6-35B-A3B share 12 comparable benchmark results. 0 of 8 categories are comparable. 3 results are unique to LFM2.5-VL-1.6B-Extract; 45 to Qwen3.6-35B-A3B.
Updated July 23, 2026- Shared results
- 12
- LFM2.5-VL-1.6B-Extract only
- 3
- Qwen3.6-35B-A3B only
- 45
- Comparable categories
- 0 / 8
Benchmark data for LFM2.5-VL-1.6B-Extract and Qwen3.6-35B-A3B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 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.
Qwen3.6-35B-A3B has the larger context window at 262K, compared with 128K for LFM2.5-VL-1.6B-Extract.
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-VL-1.6B-Extract | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Agentic | LFM2.5-VL-1.6B-ExtractNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.5 |
| Coding | LFM2.5-VL-1.6B-ExtractNot measured | MarginNo overlap | Qwen3.6-35B-A3B73.8 |
| Knowledge | LFM2.5-VL-1.6B-ExtractNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.4 |
| Math | LFM2.5-VL-1.6B-ExtractNot measured | MarginNo overlap | Qwen3.6-35B-A3B88.2 |
| Multimodal | LFM2.5-VL-1.6B-ExtractNot measured | MarginNo overlap | Qwen3.6-35B-A3B76.3 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | LFM2.5-VL-1.6B-Extract | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | LFM2.5-VL-1.6B-ExtractNot available | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | LFM2.5-VL-1.6B-ExtractNot available | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | LFM2.5-VL-1.6B-ExtractNot available | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | LFM2.5-VL-1.6B-Extract128K | Qwen3.6-35B-A3B262K | Qwen3.6-35B-A3B lists the larger context window. |
Benchmark Deep Dive
Agentic15 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 8.5% | 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 |
Coding8 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-SciCodeSource | 3.0% | 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-VL-1.6B-Extract | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 1.0% | 31.6% | Qwen3.6-35B-A3B leads |
| AA-GPQA DiamondSource | 28.9% | 84.1% | Qwen3.6-35B-A3B leads |
| AA-HLESource | 5.1% | 20.2% | Qwen3.6-35B-A3B leads |
| AA-Omniscience IndexSource | -83.9% | -21.4% | Qwen3.6-35B-A3B leads |
| AA-Omniscience AccuracySource | 5.2% | 18.9% | Qwen3.6-35B-A3B leads |
| AA-Omniscience Hallucination RateSource | 94.0% | 49.7% | 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 |
Math5 benchmarks
Multimodal18 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| Liquid Extract JSON ValiditySource | 99.6% | — | Not comparable |
| Liquid Extract F1Source | 99.6% | — | Not comparable |
| Liquid Extract VLM JudgeSource | 90.6% | — | Not comparable |
| AA-MMMU-ProSource | 26.5% | 75.0% | Qwen3.6-35B-A3B leads |
| 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 |
Inst. Following1 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| AA-IFBenchSource | 33.1% | 64.4% | Qwen3.6-35B-A3B leads |
Frequently Asked Questions (2)
Can I compare LFM2.5-VL-1.6B-Extract and Qwen3.6-35B-A3B 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.
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