DeepSeek V3 vs LFM2.5-VL-450M
Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verdict
DeepSeek V3 leads for most workloads.
Based on BenchLM composite scores, July 2026.
DeepSeek V3
40
LFM2.5-VL-450M
35
Pick DeepSeek V3 if you want the stronger benchmark profile. LFM2.5-VL-450M only becomes the better choice if you want the cheaper token bill.
Category Radar
Head-to-Head by Category
Category Breakdown
| Benchmark | DeepSeek V3 | Δ | LFM2.5-VL-450M |
|---|---|---|---|
| Knowledge | 72.8 | ← 52.3 | 20.5 |
| Inst. Following | 86.1 | ← 24.9 | 61.2 |
| Coding | 39.2 | — | — |
Operational Comparison
DeepSeek V3
LFM2.5-VL-450M
$0.27 / $1.1
$0 / $0
N/A
N/A
N/A
N/A
128K
128K
Quick Verdict
Pick DeepSeek V3 if you want the stronger benchmark profile. LFM2.5-VL-450M only becomes the better choice if you want the cheaper token bill.
DeepSeek V3 is clearly ahead on the provisional aggregate, 40 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V3's sharpest advantage is in knowledge, where it averages 72.8 against 20.5. The single biggest benchmark swing on the page is MMLU-Pro, 75.9% to 19.3%.
DeepSeek V3 is also the more expensive model on tokens at $0.27 input / $1.10 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2.5-VL-450M. That is roughly Infinityx on output cost alone.
Benchmark Deep Dive
Frequently Asked Questions (3)
Which is better, DeepSeek V3 or LFM2.5-VL-450M?
DeepSeek V3 is ahead on BenchLM's provisional leaderboard, 40 to 35. The biggest single separator in this matchup is MMLU-Pro, where the scores are 75.9% and 19.3%.
Which is better for knowledge tasks, DeepSeek V3 or LFM2.5-VL-450M?
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 72.8 versus 20.5. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Which is better for instruction following, DeepSeek V3 or LFM2.5-VL-450M?
DeepSeek V3 has the edge for instruction following in this comparison, averaging 86.1 versus 61.2. Inside this category, IFEval is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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