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Model comparison

Gemma 4 31B vs LFM2.5-VL-1.6B-Extract

Data verified

Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

61.08/100
No comparison
N/A
0 category wins0 category wins

Public leaderboard positions: Gemma 4 31B #43 (Supported); 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. Gemma 4 31B and LFM2.5-VL-1.6B-Extract share 12 comparable benchmark results. 0 of 8 categories are comparable. 17 results are unique to Gemma 4 31B; 3 to LFM2.5-VL-1.6B-Extract.

Updated July 23, 2026
Shared results
12
Gemma 4 31B only
17
LFM2.5-VL-1.6B-Extract only
3
Comparable categories
0 / 8

Benchmark data for Gemma 4 31B and LFM2.5-VL-1.6B-Extract 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.

Gemma 4 31B has the larger context window at 256K, 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 scores and score margins for Gemma 4 31B and LFM2.5-VL-1.6B-Extract
CategoryGemma 4 31BΔLFM2.5-VL-1.6B-Extract
CodingGemma 4 31B41.6MarginNo overlapLFM2.5-VL-1.6B-ExtractNot measured
KnowledgeGemma 4 31B52.9MarginNo overlapLFM2.5-VL-1.6B-ExtractNot measured
MultimodalGemma 4 31B76.9MarginNo overlapLFM2.5-VL-1.6B-ExtractNot measured

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGemma 4 31BLFM2.5-VL-1.6B-ExtractComparison
Input / output priceUSD per 1M tokensGemma 4 31B$0 input / $0 outputLFM2.5-VL-1.6B-ExtractNot availableA complete price comparison is not available.
Generation speedtokens per secondGemma 4 31BNot availableLFM2.5-VL-1.6B-ExtractNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGemma 4 31BNot availableLFM2.5-VL-1.6B-ExtractNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGemma 4 31B256KLFM2.5-VL-1.6B-Extract128KGemma 4 31B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGemma 4 31BLFM2.5-VL-1.6B-ExtractResult
AA Agentic IndexSource 14.4%—Not comparable
τ²-bench resultsSource 59.9%8.5%Gemma 4 31B leads
GDPval-AASource 15.2%—Not comparable
GDPval-AASource 804—Not comparable
Gert LabsSource 35.26%—Not comparable
AA EnterpriseOps-GymSource 28.3%—Not comparable
AA ITBenchSource 37.3%—Not comparable
AA Tau3 BankingSource 15.1%—Not comparable
terminalBenchHardSource 36.4%—Not comparable
Coding
BenchmarkGemma 4 31BLFM2.5-VL-1.6B-ExtractResult
SWE-RebenchSource 41.6%—Not comparable
React Native EvalsSource 75.2%—Not comparable
AA Coding IndexSource 43.4%—Not comparable
AA-SciCodeSource 43.4%3.0%Gemma 4 31B leads
Reasoning
BenchmarkGemma 4 31BLFM2.5-VL-1.6B-ExtractResult
AA-LCRSource 62.0%0.0%Gemma 4 31B leads
CritPtSource 1.4%0.0%Gemma 4 31B leads
Knowledge
BenchmarkGemma 4 31BLFM2.5-VL-1.6B-ExtractResult
GPQASource 84.3%—Not comparable
MMLU-ProSource 85.2%—Not comparable
HLESource 26.5%—Not comparable
HLE w/o toolsSource 19.5%—Not comparable
Artificial Analysis Intelligence IndexSource 29.4%1.0%Gemma 4 31B leads
AA-GPQA DiamondSource 85.7%28.9%Gemma 4 31B leads
AA-HLESource 22.7%5.1%Gemma 4 31B leads
AA-Omniscience IndexSource -45.4%-83.9%Gemma 4 31B leads
AA-Omniscience AccuracySource 19.9%5.2%Gemma 4 31B leads
AA-Omniscience Hallucination RateSource 81.6%94.0%Gemma 4 31B leads
AA Openness IndexSource 38.9%—Not comparable
Multimodal
BenchmarkGemma 4 31BLFM2.5-VL-1.6B-ExtractResult
MMMU-ProSource 76.9%—Not comparable
AA-MMMU-ProSource 73.4%26.5%Gemma 4 31B leads
Liquid Extract JSON ValiditySource —99.6%Not comparable
Liquid Extract F1Source —99.6%Not comparable
Liquid Extract VLM JudgeSource —90.6%Not comparable
Inst. Following
BenchmarkGemma 4 31BLFM2.5-VL-1.6B-ExtractResult
AA-IFBenchSource 75.6%33.1%Gemma 4 31B leads
Frequently Asked Questions (3)

Can I compare Gemma 4 31B 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 Gemma 4 31B and LFM2.5-VL-1.6B-Extract today?

Gemma 4 31B: $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.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Gemma 4 31B
API / mo$0
Self-host / mo$429
Break-even—
LFM2.5-VL-1.6B-Extract
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Model the full break-even

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Last updated: July 23, 2026

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