Model comparison
Claude Opus 4.7 (Adaptive) vs DeepSeek V3
Head-to-head evidence from 18 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 V3 #147 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 (Adaptive) and DeepSeek V3 share 18 comparable benchmark results. 2 of 8 categories are comparable. 20 results are unique to Claude Opus 4.7 (Adaptive); 4 to DeepSeek V3.
Updated July 23, 2026- Shared results
- 18
- Claude Opus 4.7 (Adaptive) only
- 20
- DeepSeek V3 only
- 4
- Comparable categories
- 2 / 8
Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 evidence categories; 2 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 44.97. 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 coding, where it averages 78.6 against 38.9. The single biggest benchmark swing on the page is SWE-bench Verified, 87.6% to 42%. DeepSeek V3 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Opus 4.7 (Adaptive) is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. That is roughly 22.7x on output cost alone. Claude Opus 4.7 (Adaptive) is the reasoning model in the pair, while DeepSeek V3 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 4.7 (Adaptive) gives you the larger context window at 1M, compared with 128K for DeepSeek V3.
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 V3 |
|---|---|---|---|
| Coding | Claude Opus 4.7 (Adaptive)78.6 | Margin← 39.7 | DeepSeek V338.9 |
| Knowledge | Claude Opus 4.7 (Adaptive)60.0 | Margin→ 12.7 | DeepSeek V372.7 |
| Agentic | Claude Opus 4.7 (Adaptive)75.1 | MarginNo overlap | DeepSeek V3Not measured |
| Reasoning | Claude Opus 4.7 (Adaptive)75.8 | MarginNo overlap | DeepSeek V3Not measured |
| Math | Claude Opus 4.7 (Adaptive)Not measured | MarginNo overlap | DeepSeek V31.7 |
| Multimodal | Claude Opus 4.7 (Adaptive)65.1 | MarginNo overlap | DeepSeek V3Not measured |
| Inst. Following | Claude Opus 4.7 (Adaptive)Not measured | MarginNo overlap | DeepSeek V386.1 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 87.6%B 42%Winner: Claude Opus 4.7 (Adaptive)Δ 45.6SWE-bench Verified: Claude Opus 4.7 (Adaptive) scored 87.6%; DeepSeek V3 scored 42%. Claude Opus 4.7 (Adaptive) wins this benchmark. - Source ↗
GPQA
KnowledgeA 94.2%B 59.1%Winner: Claude Opus 4.7 (Adaptive)Δ 35.1GPQA: Claude Opus 4.7 (Adaptive) scored 94.2%; DeepSeek V3 scored 59.1%. 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 V3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7 (Adaptive)$5 input / $25 output | DeepSeek V3$0.27 input / $1.1 output | DeepSeek V3 has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.7 (Adaptive)Not available | DeepSeek V3Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7 (Adaptive)Not available | DeepSeek V3Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.7 (Adaptive)1M | DeepSeek V3128K | Claude Opus 4.7 (Adaptive) lists the larger context window. |
Benchmark Deep Dive
Agentic12 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | DeepSeek V3 | Result |
|---|---|---|---|
| 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% | 1.6% | Claude Opus 4.7 (Adaptive) leads |
| τ²-bench resultsSource | 88.6% | 22.8% | Claude Opus 4.7 (Adaptive) leads |
| GDPval-AASource | 49.8% | 0.0% | Claude Opus 4.7 (Adaptive) leads |
| GDPval-AASource | 1495 | 217 | Claude Opus 4.7 (Adaptive) leads |
| OSWorld 2.0Source | 18.2% | — | Not comparable |
| JobBenchSource | 45.9% | — | Not comparable |
| AA ITBenchSource | 46.7% | — | Not comparable |
CodingClaude Opus 4.7 (Adaptive) wins6 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | DeepSeek V3 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 87.6% | 42% | Claude Opus 4.7 (Adaptive) leads |
| SWE-bench ProSource | 64.3% | — | Not comparable |
| Terminal-Bench 2.0Source | 69.4% | — | Not comparable |
| AA Coding IndexSource | 73.6% | 23.0% | Claude Opus 4.7 (Adaptive) leads |
| AA-SciCodeSource | 54.5% | 35.4% | Claude Opus 4.7 (Adaptive) leads |
| LiveCodeBenchSource | — | 37.6% | Not comparable |
Reasoning4 benchmarks
KnowledgeDeepSeek V3 wins11 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | DeepSeek V3 | Result |
|---|---|---|---|
| GPQASource | 94.2% | 59.1% | Claude Opus 4.7 (Adaptive) leads |
| 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% | 14.2% | Claude Opus 4.7 (Adaptive) leads |
| AA-GPQA DiamondSource | 91.4% | 55.7% | Claude Opus 4.7 (Adaptive) leads |
| AA-HLESource | 39.6% | 3.6% | Claude Opus 4.7 (Adaptive) leads |
| AA-Omniscience IndexSource | 26.2% | -41.3% | Claude Opus 4.7 (Adaptive) leads |
| AA-Omniscience AccuracySource | 45.8% | 25.4% | Claude Opus 4.7 (Adaptive) leads |
| AA-Omniscience Hallucination RateSource | 36.2% | 89.4% | Claude Opus 4.7 (Adaptive) leads |
| MMLU-ProSource | — | 75.9% | Not comparable |
Math2 benchmarks
Multimodal5 benchmarks
Frequently Asked Questions (3)
Which is better, Claude Opus 4.7 (Adaptive) or DeepSeek V3?
Claude Opus 4.7 (Adaptive) is ahead on BenchLM's BenchAlign leaderboard, 66.27 to 44.97. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 87.6% and 42%.
Which is better for knowledge tasks, Claude Opus 4.7 (Adaptive) or DeepSeek V3?
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 72.7 versus 60. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, Claude Opus 4.7 (Adaptive) or DeepSeek V3?
Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 78.6 versus 38.9. Inside this category, AA Coding Index 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.
Related Comparisons
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.