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Model comparison

Claude Opus 4.7 (Adaptive) vs LFM2-24B-A2B

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
66.27/100
No comparison
LiquidAI
N/A
0 category wins0 category wins

Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); LFM2-24B-A2B #197 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 (Adaptive) and LFM2-24B-A2B share 0 comparable benchmark results. 0 of 8 categories are comparable. 38 results are unique to Claude Opus 4.7 (Adaptive); 0 to LFM2-24B-A2B.

Updated July 23, 2026
Shared results
0
Claude Opus 4.7 (Adaptive) only
38
LFM2-24B-A2B only
0
Comparable categories
0 / 8

Benchmark data for Claude Opus 4.7 (Adaptive) and LFM2-24B-A2B 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 LFM2-24B-A2B yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.

Claude Opus 4.7 (Adaptive) is priced at $5.00 input / $25.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2-24B-A2B. Claude Opus 4.7 (Adaptive) has the larger context window at 1M, compared with 32K for LFM2-24B-A2B.

Operational comparison

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

MetricClaude Opus 4.7 (Adaptive)LFM2-24B-A2BComparison
Input / output priceUSD per 1M tokensClaude Opus 4.7 (Adaptive)$5 input / $25 outputLFM2-24B-A2B$0 input / $0 outputLFM2-24B-A2B has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.7 (Adaptive)Not availableLFM2-24B-A2B92 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7 (Adaptive)Not availableLFM2-24B-A2B0.42 sA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.7 (Adaptive)1MLFM2-24B-A2B32KClaude Opus 4.7 (Adaptive) lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.7 (Adaptive)LFM2-24B-A2BResult
Terminal-Bench 2.0Source 69.4%Not comparable
BrowseCompSource 79.3%Not comparable
MCP AtlasSource 77.3%Not comparable
OSWorld-VerifiedSource 78%Not comparable
CyberGymSource 73.1%Not comparable
AA Agentic IndexSource 44.4%Not comparable
τ²-bench resultsSource 88.6%Not comparable
GDPval-AASource 49.8%Not comparable
GDPval-AASource 1495Not comparable
OSWorld 2.0Source 18.2%Not comparable
JobBenchSource 45.9%Not comparable
AA ITBenchSource 46.7%Not comparable
Coding
BenchmarkClaude Opus 4.7 (Adaptive)LFM2-24B-A2BResult
SWE-bench VerifiedSource 87.6%Not comparable
SWE-bench ProSource 64.3%Not comparable
Terminal-Bench 2.0Source 69.4%Not comparable
AA Coding IndexSource 73.6%Not comparable
AA-SciCodeSource 54.5%Not comparable
Reasoning
BenchmarkClaude Opus 4.7 (Adaptive)LFM2-24B-A2BResult
MRCR v2 128K-256KSource 59.2%Not comparable
ARC-AGI-2Source 75.8%Not comparable
AA-LCRSource 70.3%Not comparable
CritPtSource 12.0%Not comparable
Knowledge
BenchmarkClaude Opus 4.7 (Adaptive)LFM2-24B-A2BResult
GPQASource 94.2%Not comparable
GPQA-DSource 94.2%Not comparable
HLESource 54.7%Not comparable
HLE w/o toolsSource 46.9%Not comparable
Artificial Analysis Intelligence IndexSource 53.5%Not comparable
AA-GPQA DiamondSource 91.4%Not comparable
AA-HLESource 39.6%Not comparable
AA-Omniscience IndexSource 26.2%Not comparable
AA-Omniscience AccuracySource 45.8%Not comparable
AA-Omniscience Hallucination RateSource 36.2%Not comparable
Math
BenchmarkClaude Opus 4.7 (Adaptive)LFM2-24B-A2BResult
FrontierMath (legacy)Source 43.8%Not comparable
Multimodal
BenchmarkClaude Opus 4.7 (Adaptive)LFM2-24B-A2BResult
OfficeQA ProSource 43.6%Not comparable
CharXivSource 91%Not comparable
CharXiv w/o toolsSource 82.1%Not comparable
AA-MMMU-ProSource 78.8%Not comparable
Design Arena WebsiteSource 1325Not comparable
Inst. Following
BenchmarkClaude Opus 4.7 (Adaptive)LFM2-24B-A2BResult
AA-IFBenchSource 58.6%Not comparable
Frequently Asked Questions (3)

Can I compare Claude Opus 4.7 (Adaptive) and LFM2-24B-A2B 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 Claude Opus 4.7 (Adaptive) and LFM2-24B-A2B today?

Claude Opus 4.7 (Adaptive): $5.00 input / $25.00 output per 1M tokens LFM2-24B-A2B: $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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Last updated: July 23, 2026

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