Model comparison
Claude Opus 4.7 (Adaptive) vs DeepSeek V4 Flash (High)
Head-to-head evidence from 25 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); DeepSeek V4 Flash (High) #92 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 (Adaptive) and DeepSeek V4 Flash (High) share 25 comparable benchmark results. 3 of 8 categories are comparable. 13 results are unique to Claude Opus 4.7 (Adaptive); 13 to DeepSeek V4 Flash (High).
Updated July 23, 2026- Shared results
- 25
- Claude Opus 4.7 (Adaptive) only
- 13
- DeepSeek V4 Flash (High) only
- 13
- Comparable categories
- 3 / 8
Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. DeepSeek V4 Flash (High) only becomes the better choice if you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 25 shared benchmark results across 6 evidence categories; 3 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 4.7 (Adaptive) is clearly ahead on the BenchAlign aggregate, 66.27 to 53.95. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.7 (Adaptive)'s sharpest advantage is in agentic, where it averages 75.1 against 55.3. The single biggest benchmark swing on the page is BrowseComp, 79.3% to 53.5%.
Claude Opus 4.7 (Adaptive) is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (High). That is roughly 89.3x on output cost alone.
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 4.7 (Adaptive) | Δ | DeepSeek V4 Flash (High) |
|---|---|---|---|
| Agentic | Claude Opus 4.7 (Adaptive)75.1 | Margin← 19.8 | DeepSeek V4 Flash (High)55.3 |
| Coding | Claude Opus 4.7 (Adaptive)78.6 | Margin← 10.1 | DeepSeek V4 Flash (High)68.5 |
| Knowledge | Claude Opus 4.7 (Adaptive)60.0 | Margin← 7.9 | DeepSeek V4 Flash (High)52.1 |
| Reasoning | Claude Opus 4.7 (Adaptive)75.8 | MarginNo overlap | DeepSeek V4 Flash (High)Not measured |
| Math | Claude Opus 4.7 (Adaptive)Not measured | MarginNo overlap | DeepSeek V4 Flash (High)91.9 |
| Multimodal | Claude Opus 4.7 (Adaptive)65.1 | MarginNo overlap | DeepSeek V4 Flash (High)Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
BrowseComp
AgenticA 79.3%B 53.5%Winner: Claude Opus 4.7 (Adaptive)Δ 25.8BrowseComp: Claude Opus 4.7 (Adaptive) scored 79.3%; DeepSeek V4 Flash (High) scored 53.5%. Claude Opus 4.7 (Adaptive) wins this benchmark. - Source ↗
HLE
KnowledgeA 54.7%B 29.4%Winner: Claude Opus 4.7 (Adaptive)Δ 25.3HLE: Claude Opus 4.7 (Adaptive) scored 54.7%; DeepSeek V4 Flash (High) scored 29.4%. Claude Opus 4.7 (Adaptive) wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 69.4%B 56.6%Winner: Claude Opus 4.7 (Adaptive)Δ 12.8Terminal-Bench 2.0: Claude Opus 4.7 (Adaptive) scored 69.4%; DeepSeek V4 Flash (High) scored 56.6%. Claude Opus 4.7 (Adaptive) wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 64.3%B 52.3%Winner: Claude Opus 4.7 (Adaptive)Δ 12SWE-bench Pro: Claude Opus 4.7 (Adaptive) scored 64.3%; DeepSeek V4 Flash (High) scored 52.3%. Claude Opus 4.7 (Adaptive) wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 87.6%B 78.6%Winner: Claude Opus 4.7 (Adaptive)Δ 9SWE-bench Verified: Claude Opus 4.7 (Adaptive) scored 87.6%; DeepSeek V4 Flash (High) scored 78.6%. Claude Opus 4.7 (Adaptive) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.7 (Adaptive) | DeepSeek V4 Flash (High) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7 (Adaptive)$5 input / $25 output | DeepSeek V4 Flash (High)$0.14 input / $0.28 output | DeepSeek V4 Flash (High) has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.7 (Adaptive)Not available | DeepSeek V4 Flash (High)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7 (Adaptive)Not available | DeepSeek V4 Flash (High)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.7 (Adaptive)1M | DeepSeek V4 Flash (High)1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticClaude Opus 4.7 (Adaptive) wins14 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 69.4% | 56.6% | Claude Opus 4.7 (Adaptive) leads |
| BrowseCompSource | 79.3% | 53.5% | Claude Opus 4.7 (Adaptive) leads |
| MCP AtlasSource | 77.3% | 67.4% | Claude Opus 4.7 (Adaptive) leads |
| OSWorld-VerifiedSource | 78% | — | Not comparable |
| CyberGymSource | 73.1% | — | Not comparable |
| AA Agentic IndexSource | 44.4% | 28.2% | Claude Opus 4.7 (Adaptive) leads |
| τ²-bench resultsSource | 88.6% | 95.6% | DeepSeek V4 Flash (High) leads |
| GDPval-AASource | 49.8% | 32.4% | Claude Opus 4.7 (Adaptive) leads |
| GDPval-AASource | 1495 | 1147 | Claude Opus 4.7 (Adaptive) leads |
| OSWorld 2.0Source | 18.2% | — | Not comparable |
| JobBenchSource | 45.9% | — | Not comparable |
| AA ITBenchSource | 46.7% | — | Not comparable |
| HLE w/ toolsSource | — | 40.3% | Not comparable |
| ToolathlonSource | — | 43.5% | Not comparable |
CodingClaude Opus 4.7 (Adaptive) wins7 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 87.6% | 78.6% | Claude Opus 4.7 (Adaptive) leads |
| SWE-bench ProSource | 64.3% | 52.3% | Claude Opus 4.7 (Adaptive) leads |
| Terminal-Bench 2.0Source | 69.4% | 56.6% | Claude Opus 4.7 (Adaptive) leads |
| AA Coding IndexSource | 73.6% | 52.0% | Claude Opus 4.7 (Adaptive) leads |
| AA-SciCodeSource | 54.5% | 42.0% | Claude Opus 4.7 (Adaptive) leads |
| CodeforcesSource | — | 2816.0 | Not comparable |
| SWE MultilingualSource | — | 70.2% | Not comparable |
Reasoning6 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| MRCR v2 128K-256KSource | 59.2% | — | Not comparable |
| ARC-AGI-2Source | 75.8% | — | Not comparable |
| AA-LCRSource | 70.3% | 62.7% | Claude Opus 4.7 (Adaptive) leads |
| CritPtSource | 12.0% | 3.4% | Claude Opus 4.7 (Adaptive) leads |
| MRCR 1MSource | — | 76.9% | Not comparable |
| CorpusQA 1MSource | — | 59.3% | Not comparable |
KnowledgeClaude Opus 4.7 (Adaptive) wins13 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| GPQASource | 94.2% | 87.4% | Claude Opus 4.7 (Adaptive) leads |
| GPQA-DSource | 94.2% | 87.4% | Claude Opus 4.7 (Adaptive) leads |
| HLESource | 54.7% | 29.4% | Claude Opus 4.7 (Adaptive) leads |
| HLE w/o toolsSource | 46.9% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 53.5% | 37.5% | Claude Opus 4.7 (Adaptive) leads |
| AA-GPQA DiamondSource | 91.4% | 86.7% | Claude Opus 4.7 (Adaptive) leads |
| AA-HLESource | 39.6% | 27.8% | Claude Opus 4.7 (Adaptive) leads |
| AA-Omniscience IndexSource | 26.2% | -22.3% | Claude Opus 4.7 (Adaptive) leads |
| AA-Omniscience AccuracySource | 45.8% | 35.5% | Claude Opus 4.7 (Adaptive) leads |
| AA-Omniscience Hallucination RateSource | 36.2% | 89.7% | Claude Opus 4.7 (Adaptive) leads |
| MMLU-ProSource | — | 86.4% | Not comparable |
| SimpleQASource | — | 28.9% | Not comparable |
| Chinese-SimpleQASource | — | 73.2% | Not comparable |
Math5 benchmarks
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| AA-IFBenchSource | 58.6% | 73.5% | DeepSeek V4 Flash (High) leads |
Frequently Asked Questions (4)
Which is better, Claude Opus 4.7 (Adaptive) or DeepSeek V4 Flash (High)?
Claude Opus 4.7 (Adaptive) is ahead on BenchLM's BenchAlign leaderboard, 66.27 to 53.95. The biggest single separator in this matchup is BrowseComp, where the scores are 79.3% and 53.5%.
Which is better for knowledge tasks, Claude Opus 4.7 (Adaptive) or DeepSeek V4 Flash (High)?
Claude Opus 4.7 (Adaptive) has the edge for knowledge tasks in this comparison, averaging 60 versus 52.1. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Opus 4.7 (Adaptive) or DeepSeek V4 Flash (High)?
Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 78.6 versus 68.5. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Claude Opus 4.7 (Adaptive) or DeepSeek V4 Flash (High)?
Claude Opus 4.7 (Adaptive) has the edge for agentic tasks in this comparison, averaging 75.1 versus 55.3. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Related Comparisons
- Claude Opus 4.7 (Adaptive) vs Claude Opus 4.7
- DeepSeek V4 Flash (High) vs DeepSeek V4 Pro (Max)
- DeepSeek V4 Flash (High) vs DeepSeek V4 Pro (High)
- DeepSeek V4 Flash (High) vs DeepSeek V4 Flash (Max)
- DeepSeek V4 Flash (High) vs DeepSeek V4 Pro
- DeepSeek V4 Flash (High) vs DeepSeek V4 Pro Base
- DeepSeek V4 Flash (High) vs DeepSeek V4 Flash Base
- DeepSeek V4 Flash (High) vs DeepSeek V4 Flash
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