Model comparison
Claude Opus 4.8 vs LFM2.5-VL-450M
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: Claude Opus 4.8 #3; LFM2.5-VL-450M unranked
Evidence parity. Claude Opus 4.8 and LFM2.5-VL-450M share 1 comparable benchmark result. 1 of 8 categories are comparable. 52 results are unique to Claude Opus 4.8; 6 to LFM2.5-VL-450M.
Updated July 12, 2026- Shared results
- 1
- Claude Opus 4.8 only
- 52
- LFM2.5-VL-450M only
- 6
- Comparable categories
- 1 / 8
Pick Claude Opus 4.8 if you want the stronger benchmark profile. LFM2.5-VL-450M only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Claude Opus 4.8 is clearly ahead on the provisional aggregate, 85 to 34. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.8's sharpest advantage is in knowledge, where it averages 62.7 against 20.5. The single biggest benchmark swing on the page is GPQA, 93.6% to 25.7%.
Claude Opus 4.8 is also the more expensive model on tokens at $5.00 input / $25.00 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. Claude Opus 4.8 is the reasoning model in the pair, while LFM2.5-VL-450M is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Claude Opus 4.8 gives you the larger context window at 1M, compared with 128K for LFM2.5-VL-450M.
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 | Claude Opus 4.8 | Δ | LFM2.5-VL-450M |
|---|---|---|---|
| Knowledge | Claude Opus 4.862.7 | Margin← 42.2 | LFM2.5-VL-450M20.5 |
| Agentic | Claude Opus 4.880.3 | MarginNo overlap | LFM2.5-VL-450MNot measured |
| Coding | Claude Opus 4.876.4 | MarginNo overlap | LFM2.5-VL-450MNot measured |
| Math | Claude Opus 4.853.9 | MarginNo overlap | LFM2.5-VL-450MNot measured |
| Multimodal | Claude Opus 4.877.0 | MarginNo overlap | LFM2.5-VL-450MNot measured |
| Inst. Following | Claude Opus 4.8Not measured | MarginNo overlap | LFM2.5-VL-450M61.2 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 93.6%B 25.7%Winner: Claude Opus 4.8Δ 67.9GPQA: Claude Opus 4.8 scored 93.6%; LFM2.5-VL-450M scored 25.7%. Claude Opus 4.8 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.8 | LFM2.5-VL-450M | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.8$5 input / $25 output | LFM2.5-VL-450M$0 input / $0 output | LFM2.5-VL-450M has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.8Not available | LFM2.5-VL-450MNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.8Not available | LFM2.5-VL-450MNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.81M | LFM2.5-VL-450M128K | Claude Opus 4.8 lists the larger context window. |
Benchmark Deep Dive
Agentic20 benchmarks
| Benchmark | Claude Opus 4.8 | LFM2.5-VL-450M | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 74.6% | — | Not comparable |
| BrowseCompSource | 84.3% | — | Not comparable |
| DeepSearchQASource | 93.1% | — | Not comparable |
| OSWorld-VerifiedSource | 83.4% | — | Not comparable |
| Finance Agent v2Source | 53.9% | — | Not comparable |
| GDPval-AASource | 1600 | — | Not comparable |
| MCP AtlasSource | 82.2% | — | Not comparable |
| ToolathlonSource | 59.9% | — | Not comparable |
| Gert LabsSource | 72.97% | — | Not comparable |
| AA Agentic IndexSource | 47.2% | — | Not comparable |
| Tau2-TelecomSource | 94.4% | — | Not comparable |
| GDPval-AASource | 55.0% | — | Not comparable |
| ResearchClawBenchSource | 21.1% | — | Not comparable |
| OSWorld 2.0Source | 20.6% | — | Not comparable |
| AA BriefcaseSource | 1354 | — | Not comparable |
| AA AutomationBenchSource | 48.5% | — | Not comparable |
| AA EnterpriseOps-GymSource | 44.0% | — | Not comparable |
| AA Harvey LABSource | 7.5% | — | Not comparable |
| AA Tau3 BankingSource | 27.6% | — | Not comparable |
| BFCL v4Source | — | 21.1% | Not comparable |
Coding12 benchmarks
| Benchmark | Claude Opus 4.8 | LFM2.5-VL-450M | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 88.6% | — | Not comparable |
| SWE-bench ProSource | 69.2% | — | Not comparable |
| SWE MultilingualSource | 84.4% | — | Not comparable |
| SWE MultimodalSource | 38.4% | — | Not comparable |
| Terminal-Bench 2.0Source | 74.6% | — | Not comparable |
| cursorBench31Source | 58.4% | — | Not comparable |
| cursorBench32Source | 62.3% | — | Not comparable |
| AA Coding IndexSource | 74.3% | — | Not comparable |
| Terminal-Bench HardSource | 58.3% | — | Not comparable |
| AA-SciCodeSource | 53.5% | — | Not comparable |
| FrontierCodeSource | 46.5% | — | Not comparable |
| AA Terminal-Bench 2.1Source | 84.6% | — | Not comparable |
Reasoning2 benchmarks
KnowledgeClaude Opus 4.8 wins11 benchmarks
| Benchmark | Claude Opus 4.8 | LFM2.5-VL-450M | Result |
|---|---|---|---|
| GPQASource | 93.6% | 25.7% | Claude Opus 4.8 leads |
| GPQA-DSource | 93.6% | — | Not comparable |
| HLESource | 57.9% | — | Not comparable |
| HLE w/o toolsSource | 49.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 55.7% | — | Not comparable |
| AA-GPQA DiamondSource | 92.0% | — | Not comparable |
| AA-HLESource | 45.7% | — | Not comparable |
| AA-Omniscience IndexSource | 27.4% | — | Not comparable |
| AA-Omniscience AccuracySource | 46.6% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 35.9% | — | Not comparable |
| MMLU-ProSource | — | 19.3% | Not comparable |
Math3 benchmarks
Multilingual1 benchmarks
| Benchmark | Claude Opus 4.8 | LFM2.5-VL-450M | Result |
|---|---|---|---|
| INCLUDESource | 87.6% | — | Not comparable |
Multimodal8 benchmarks
| Benchmark | Claude Opus 4.8 | LFM2.5-VL-450M | Result |
|---|---|---|---|
| OfficeQA ProSource | 66.2% | — | Not comparable |
| ScreenSpot ProSource | 87.9% | — | Not comparable |
| CharXivSource | 89.9% | — | Not comparable |
| CharXiv w/o toolsSource | 80.5% | — | Not comparable |
| Design Arena WebsiteSource | 1281 | — | Not comparable |
| MMMUSource | — | 32.7% | Not comparable |
| RealWorldQASource | — | 58.4% | Not comparable |
| CountBenchSource | — | 73.3% | Not comparable |
Frequently Asked Questions (2)
Which is better, Claude Opus 4.8 or LFM2.5-VL-450M?
Claude Opus 4.8 is ahead on BenchLM's provisional leaderboard, 85 to 34. The biggest single separator in this matchup is GPQA, where the scores are 93.6% and 25.7%.
Which is better for knowledge tasks, Claude Opus 4.8 or LFM2.5-VL-450M?
Claude Opus 4.8 has the edge for knowledge tasks in this comparison, averaging 62.7 versus 20.5. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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