Model comparison
LFM2.5-VL-1.6B-Extract vs Muse Spark 1.1
Head-to-head evidence from 9 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: LFM2.5-VL-1.6B-Extract unranked (Not scored); Muse Spark 1.1 #6 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. LFM2.5-VL-1.6B-Extract and Muse Spark 1.1 share 9 comparable benchmark results. 0 of 8 categories are comparable. 6 results are unique to LFM2.5-VL-1.6B-Extract; 30 to Muse Spark 1.1.
Updated July 23, 2026- Shared results
- 9
- LFM2.5-VL-1.6B-Extract only
- 6
- Muse Spark 1.1 only
- 30
- Comparable categories
- 0 / 8
Benchmark data for LFM2.5-VL-1.6B-Extract and Muse Spark 1.1 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 9 shared benchmark results across 3 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.
Muse Spark 1.1 has the larger context window at 1M, 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 | Muse Spark 1.1 |
|---|---|---|---|
| Agentic | LFM2.5-VL-1.6B-ExtractNot measured | MarginNo overlap | Muse Spark 1.180.4 |
| Coding | LFM2.5-VL-1.6B-ExtractNot measured | MarginNo overlap | Muse Spark 1.161.5 |
| Knowledge | LFM2.5-VL-1.6B-ExtractNot measured | MarginNo overlap | Muse Spark 1.162.1 |
| Multimodal | LFM2.5-VL-1.6B-ExtractNot measured | MarginNo overlap | Muse Spark 1.188.4 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | LFM2.5-VL-1.6B-Extract | Muse Spark 1.1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | LFM2.5-VL-1.6B-ExtractNot available | Muse Spark 1.1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | LFM2.5-VL-1.6B-ExtractNot available | Muse Spark 1.1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | LFM2.5-VL-1.6B-ExtractNot available | Muse Spark 1.1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | LFM2.5-VL-1.6B-Extract128K | Muse Spark 1.11M | Muse Spark 1.1 lists the larger context window. |
Benchmark Deep Dive
Agentic21 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Muse Spark 1.1 | Result |
|---|---|---|---|
| τ²-bench resultsSource | 8.5% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 80% | Not comparable |
| MCP AtlasSource | — | 88.1% | Not comparable |
| ToolathlonSource | — | 75.6% | Not comparable |
| OSWorld-VerifiedSource | — | 80.8% | Not comparable |
| DeepSearchQASource | — | 84.9% | Not comparable |
| CyberGymSource | — | 59.0% | Not comparable |
| Finance Agent v2Source | — | 57.2% | Not comparable |
| deepSweSource | — | 53.3% | Not comparable |
| OSWorld 2.0Source | — | 14.2% | Not comparable |
| JobBenchSource | — | 54.7% | Not comparable |
| CybenchSource | — | 92.9% | Not comparable |
| ExploitGymSource | — | 0.8% | Not comparable |
| AA Agentic IndexSource | — | 37.5% | Not comparable |
| GDPval-AASource | — | 43.7% | Not comparable |
| GDPval-AASource | — | 1374 | Not comparable |
| AA BriefcaseSource | — | 863 | Not comparable |
| AA AutomationBenchSource | — | 42.8% | Not comparable |
| AA Harvey LABSource | — | 93.1% | Not comparable |
| AA Tau3 BankingSource | — | 25.2% | Not comparable |
| aaTerminalBench21Source | — | 77.9% | Not comparable |
Coding4 benchmarks
Reasoning3 benchmarks
Knowledge9 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Muse Spark 1.1 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 1.0% | 50.6% | Muse Spark 1.1 leads |
| AA-GPQA DiamondSource | 28.9% | 89.8% | Muse Spark 1.1 leads |
| AA-HLESource | 5.1% | 45.1% | Muse Spark 1.1 leads |
| AA-Omniscience IndexSource | -83.9% | 18.0% | Muse Spark 1.1 leads |
| AA-Omniscience AccuracySource | 5.2% | 40.6% | Muse Spark 1.1 leads |
| AA-Omniscience Hallucination RateSource | 94.0% | 38.1% | Muse Spark 1.1 leads |
| HLESource | — | 62.1% | Not comparable |
| HLE w/o toolsSource | — | 52.2% | Not comparable |
| HealthBench ProfessionalSource | — | 59.3% | Not comparable |
Multimodal7 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Muse Spark 1.1 | 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% | — | Not comparable |
| CharXivSource | — | 88.4% | Not comparable |
| BabyVisionSource | — | 76.3% | Not comparable |
| Design Arena WebsiteSource | — | 1299 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Muse Spark 1.1 | Result |
|---|---|---|---|
| AA-IFBenchSource | 33.1% | — | Not comparable |
Frequently Asked Questions (2)
Can I compare LFM2.5-VL-1.6B-Extract and Muse Spark 1.1 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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