Model comparison
Granite-4.0-350M vs LFM2.5-VL-1.6B-Extract
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Granite-4.0-350M #181 (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. Granite-4.0-350M and LFM2.5-VL-1.6B-Extract share 11 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to Granite-4.0-350M; 4 to LFM2.5-VL-1.6B-Extract.
Updated July 23, 2026- Shared results
- 11
- Granite-4.0-350M only
- 0
- LFM2.5-VL-1.6B-Extract only
- 4
- Comparable categories
- 0 / 8
Benchmark data for Granite-4.0-350M and LFM2.5-VL-1.6B-Extract is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 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.
LFM2.5-VL-1.6B-Extract has the larger context window at 128K, compared with 32K for Granite-4.0-350M.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Granite-4.0-350M | LFM2.5-VL-1.6B-Extract | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Granite-4.0-350M$0 input / $0 output | LFM2.5-VL-1.6B-ExtractNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Granite-4.0-350MNot available | LFM2.5-VL-1.6B-ExtractNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Granite-4.0-350MNot available | LFM2.5-VL-1.6B-ExtractNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Granite-4.0-350M32K | LFM2.5-VL-1.6B-Extract128K | LFM2.5-VL-1.6B-Extract lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | Granite-4.0-350M | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| τ²-bench resultsSource | 13.2% | 8.5% | Granite-4.0-350M leads |
Coding1 benchmarks
| Benchmark | Granite-4.0-350M | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-SciCodeSource | 0.9% | 3.0% | LFM2.5-VL-1.6B-Extract leads |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Granite-4.0-350M | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 1.0% | 1.0% | LFM2.5-VL-1.6B-Extract leads |
| AA-GPQA DiamondSource | 20.3% | 28.9% | LFM2.5-VL-1.6B-Extract leads |
| AA-HLESource | 5.7% | 5.1% | Granite-4.0-350M leads |
| AA-Omniscience IndexSource | -72.1% | -83.9% | Granite-4.0-350M leads |
| AA-Omniscience AccuracySource | 3.2% | 5.2% | LFM2.5-VL-1.6B-Extract leads |
| AA-Omniscience Hallucination RateSource | 77.8% | 94.0% | Granite-4.0-350M leads |
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | Granite-4.0-350M | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-IFBenchSource | 16.8% | 33.1% | LFM2.5-VL-1.6B-Extract leads |
Frequently Asked Questions (3)
Can I compare Granite-4.0-350M 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 Granite-4.0-350M and LFM2.5-VL-1.6B-Extract today?
Granite-4.0-350M: $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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