Model comparison
Claude Opus 4.7 vs DeepSeek V4 Pro (Max)
Head-to-head evidence from 13 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.7 #12 (Supported); DeepSeek V4 Pro (Max) unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 and DeepSeek V4 Pro (Max) share 13 comparable benchmark results. 1 of 8 categories are comparable. 8 results are unique to Claude Opus 4.7; 35 to DeepSeek V4 Pro (Max).
Updated July 23, 2026- Shared results
- 13
- Claude Opus 4.7 only
- 8
- DeepSeek V4 Pro (Max) only
- 35
- Comparable categories
- 1 / 8
Treat this as a split decision. Claude Opus 4.7 makes more sense if you would rather avoid the extra latency and token burn of a reasoning model; DeepSeek V4 Pro (Max) is the better fit if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 6 evidence categories; 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 4.7 and DeepSeek V4 Pro (Max) finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Claude Opus 4.7 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro (Max). That is roughly 28.7x on output cost alone. DeepSeek V4 Pro (Max) is the reasoning model in the pair, while Claude Opus 4.7 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.
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 | Δ | DeepSeek V4 Pro (Max) |
|---|---|---|---|
| Math | Claude Opus 4.738.6 | Margin→ 56.6 | DeepSeek V4 Pro (Max)95.2 |
| Agentic | Claude Opus 4.7Not measured | MarginNo overlap | DeepSeek V4 Pro (Max)74.5 |
| Coding | Claude Opus 4.7Not measured | MarginNo overlap | DeepSeek V4 Pro (Max)70.9 |
| Knowledge | Claude Opus 4.7Not measured | MarginNo overlap | DeepSeek V4 Pro (Max)60.1 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.7 | DeepSeek V4 Pro (Max) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7$5 input / $25 output | DeepSeek V4 Pro (Max)$0.435 input / $0.87 output | DeepSeek V4 Pro (Max) has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.7Not available | DeepSeek V4 Pro (Max)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7Not available | DeepSeek V4 Pro (Max)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.71M | DeepSeek V4 Pro (Max)1M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic20 benchmarks
| Benchmark | Claude Opus 4.7 | DeepSeek V4 Pro (Max) | Result |
|---|---|---|---|
| τ²-bench resultsSource | 74% | 96.2% | DeepSeek V4 Pro (Max) leads |
| Gert LabsSource | 65.59% | — | Not comparable |
| ResearchClawBenchSource | 20.7% | — | Not comparable |
| OSWorld 2.0Source | 13.9% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 67.9% | Not comparable |
| BrowseCompSource | — | 83.4% | Not comparable |
| HLE w/ toolsSource | — | 48.2% | Not comparable |
| MCP AtlasSource | — | 73.6% | Not comparable |
| GDPval-AASource | — | 1307 | Not comparable |
| ToolathlonSource | — | 51.8% | Not comparable |
| AA Agentic IndexSource | — | 36.4% | Not comparable |
| APEX-Agents-AASource | — | 24.3% | Not comparable |
| GDPval-AASource | — | 40.4% | Not comparable |
| AA BriefcaseSource | — | 932 | Not comparable |
| AA EnterpriseOps-GymSource | — | 40.4% | Not comparable |
| AA Harvey LABSource | — | 84.4% | Not comparable |
| AA ITBenchSource | — | 38.3% | Not comparable |
| AA Tau3 BankingSource | — | 25.8% | Not comparable |
| terminalBenchHardSource | — | 46.2% | Not comparable |
| aaTerminalBench21Source | — | 64% | Not comparable |
Coding10 benchmarks
| Benchmark | Claude Opus 4.7 | DeepSeek V4 Pro (Max) | Result |
|---|---|---|---|
| Vibe Code BenchSource | 71.00% | 49.93% | Claude Opus 4.7 leads |
| React Native EvalsSource | 82.8% | — | Not comparable |
| AA-SciCodeSource | 50.1% | 50.0% | Claude Opus 4.7 leads |
| FrontierCode 1.1 MainSource | 38.5% | — | Not comparable |
| CodeforcesSource | — | 3206.0 | Not comparable |
| SWE-bench VerifiedSource | — | 80.6% | Not comparable |
| SWE-bench ProSource | — | 55.4% | Not comparable |
| SWE MultilingualSource | — | 76.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 67.9% | Not comparable |
| AA Coding IndexSource | — | 59.4% | Not comparable |
Reasoning4 benchmarks
Knowledge13 benchmarks
| Benchmark | Claude Opus 4.7 | DeepSeek V4 Pro (Max) | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 42.7% | 44.3% | DeepSeek V4 Pro (Max) leads |
| AA-GPQA DiamondSource | 88.5% | 88.8% | DeepSeek V4 Pro (Max) leads |
| AA-HLESource | 31.2% | 35.9% | DeepSeek V4 Pro (Max) leads |
| AA-Omniscience IndexSource | 14.2% | -10.0% | Claude Opus 4.7 leads |
| AA-Omniscience AccuracySource | 43.5% | 43.3% | Claude Opus 4.7 leads |
| AA-Omniscience Hallucination RateSource | 51.9% | 94.0% | Claude Opus 4.7 leads |
| MMLU-ProSource | — | 87.5% | Not comparable |
| SimpleQASource | — | 57.9% | Not comparable |
| Chinese-SimpleQASource | — | 84.4% | Not comparable |
| GPQASource | — | 90.1% | Not comparable |
| GPQA-DSource | — | 90.1% | Not comparable |
| HLESource | — | 37.7% | Not comparable |
| AA Openness IndexSource | — | 50.0% | Not comparable |
MathDeepSeek V4 Pro (Max) wins6 benchmarks
| Benchmark | Claude Opus 4.7 | DeepSeek V4 Pro (Max) | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 43.793% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 22.917% | — | Not comparable |
| HMMT Feb 2026Source | — | 95.2% | Not comparable |
| IMOAnswerBenchSource | — | 89.8% | Not comparable |
| ApexSource | — | 38.3% | Not comparable |
| Apex ShortlistSource | — | 90.2% | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 | DeepSeek V4 Pro (Max) | Result |
|---|---|---|---|
| AA-IFBenchSource | 43.6% | 76.5% | DeepSeek V4 Pro (Max) leads |
Frequently Asked Questions (2)
Which is better, Claude Opus 4.7 or DeepSeek V4 Pro (Max)?
Claude Opus 4.7 and DeepSeek V4 Pro (Max) are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for math, Claude Opus 4.7 or DeepSeek V4 Pro (Max)?
DeepSeek V4 Pro (Max) has the edge for math in this comparison, averaging 95.2 versus 38.6. Claude Opus 4.7 stays close enough that the answer can still flip depending on your workload.
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