Model comparison
DeepSeekMath V2 vs LFM2.5-VL-1.6B-Extract
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: DeepSeekMath V2 #119 (Estimated); LFM2.5-VL-1.6B-Extract unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeekMath V2 and LFM2.5-VL-1.6B-Extract share 0 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to DeepSeekMath V2; 15 to LFM2.5-VL-1.6B-Extract.
Updated July 23, 2026- Shared results
- 0
- DeepSeekMath V2 only
- 0
- LFM2.5-VL-1.6B-Extract only
- 15
- Comparable categories
- 0 / 8
Benchmark data for DeepSeekMath V2 and LFM2.5-VL-1.6B-Extract 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 DeepSeekMath V2 yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeekMath V2 | LFM2.5-VL-1.6B-Extract | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeekMath V2$0 input / $0 output | LFM2.5-VL-1.6B-ExtractNot available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeekMath V2Not available | LFM2.5-VL-1.6B-ExtractNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeekMath V2Not available | LFM2.5-VL-1.6B-ExtractNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeekMath V2128K | LFM2.5-VL-1.6B-Extract128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | DeepSeekMath V2 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| τ²-bench resultsSource | — | 8.5% | Not comparable |
Coding1 benchmarks
| Benchmark | DeepSeekMath V2 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-SciCodeSource | — | 3.0% | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | DeepSeekMath V2 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | — | 1.0% | Not comparable |
| AA-GPQA DiamondSource | — | 28.9% | Not comparable |
| AA-HLESource | — | 5.1% | Not comparable |
| AA-Omniscience IndexSource | — | -83.9% | Not comparable |
| AA-Omniscience AccuracySource | — | 5.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 94.0% | Not comparable |
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeekMath V2 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 33.1% | Not comparable |
Frequently Asked Questions (3)
Can I compare DeepSeekMath V2 and LFM2.5-VL-1.6B-Extract 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 DeepSeekMath V2 and LFM2.5-VL-1.6B-Extract today?
DeepSeekMath V2: $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.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.