Model comparison
Claude Opus 4.7 vs DeepSeek V3.2
Head-to-head evidence from 17 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
BenchAlign evidence: Claude Opus 4.7 supported; DeepSeek V3.2 supported. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 and DeepSeek V3.2 share 17 comparable benchmark results. 1 of 8 categories are comparable. 5 results are unique to Claude Opus 4.7; 3 to DeepSeek V3.2.
Updated July 15, 2026- Shared results
- 17
- Claude Opus 4.7 only
- 5
- DeepSeek V3.2 only
- 3
- Comparable categories
- 1 / 8
Pick Claude Opus 4.7 if you want the stronger benchmark profile. DeepSeek V3.2 only becomes the better choice if you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 17 shared benchmark results across 7 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 is clearly ahead on the provisional aggregate, 69 to 54. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.7's sharpest advantage is in mathematics, where it averages 38.6 against 17.1. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 43.793% to 22.100%.
Claude Opus 4.7 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 59.5x on output cost alone. Claude Opus 4.7 gives you the larger context window at 1M, compared with 128K for DeepSeek V3.2.
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 V3.2 |
|---|---|---|---|
| Math | Claude Opus 4.738.6 | Margin← 21.5 | DeepSeek V3.217.1 |
| Coding | Claude Opus 4.7Not measured | MarginNo overlap | DeepSeek V3.260.9 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 43.793%B 22.100%Winner: Claude Opus 4.7Δ 21.7FrontierMath v2 (Tiers 1-3): Claude Opus 4.7 scored 43.793%; DeepSeek V3.2 scored 22.100%. Claude Opus 4.7 wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 22.917%B 2.100%Winner: Claude Opus 4.7Δ 20.8FrontierMath v2 (Tier 4): Claude Opus 4.7 scored 22.917%; DeepSeek V3.2 scored 2.100%. Claude Opus 4.7 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 | DeepSeek V3.2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7$5 input / $25 output | DeepSeek V3.2$0.28 input / $0.42 output | DeepSeek V3.2 has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.7Not available | DeepSeek V3.235 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7Not available | DeepSeek V3.23.75 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.71M | DeepSeek V3.2128K | Claude Opus 4.7 lists the larger context window. |
Benchmark Deep Dive
Agentic6 benchmarks
Coding6 benchmarks
| Benchmark | Claude Opus 4.7 | DeepSeek V3.2 | Result |
|---|---|---|---|
| Vibe Code BenchSource | 71.00% | — | Not comparable |
| React Native EvalsSource | 82.8% | 71.5% | Claude Opus 4.7 leads |
| Terminal-Bench HardSource | 54.5% | 32.6% | Claude Opus 4.7 leads |
| AA-SciCodeSource | 50.1% | 38.7% | Claude Opus 4.7 leads |
| FrontierCodeSource | 38.5% | — | Not comparable |
| SWE-RebenchSource | — | 60.9% | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Claude Opus 4.7 | DeepSeek V3.2 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 42.7% | 24.7% | Claude Opus 4.7 leads |
| AA-GPQA DiamondSource | 88.5% | 75.1% | Claude Opus 4.7 leads |
| AA-HLESource | 31.2% | 10.5% | Claude Opus 4.7 leads |
| AA-Omniscience IndexSource | 14.2% | -46.7% | Claude Opus 4.7 leads |
| AA-Omniscience AccuracySource | 43.5% | 24.2% | Claude Opus 4.7 leads |
| AA-Omniscience Hallucination RateSource | 51.9% | 93.5% | Claude Opus 4.7 leads |
MathClaude Opus 4.7 wins2 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 | DeepSeek V3.2 | Result |
|---|---|---|---|
| AA-IFBenchSource | 43.6% | 49.0% | DeepSeek V3.2 leads |
Frequently Asked Questions (2)
Which is better, Claude Opus 4.7 or DeepSeek V3.2?
Claude Opus 4.7 is ahead on BenchLM's provisional leaderboard, 69 to 54. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 43.793% and 22.100%.
Which is better for math, Claude Opus 4.7 or DeepSeek V3.2?
Claude Opus 4.7 has the edge for math in this comparison, averaging 38.6 versus 17.1. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
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