Model comparison
Claude 3.5 Sonnet vs DeepSeek V4 Flash (High)
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude 3.5 Sonnet #132 (Estimated); DeepSeek V4 Flash (High) #92 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude 3.5 Sonnet and DeepSeek V4 Flash (High) share 2 comparable benchmark results. 3 of 8 categories are comparable. 2 results are unique to Claude 3.5 Sonnet; 36 to DeepSeek V4 Flash (High).
Updated July 23, 2026- Shared results
- 2
- Claude 3.5 Sonnet only
- 2
- DeepSeek V4 Flash (High) only
- 36
- Comparable categories
- 3 / 8
Pick DeepSeek V4 Flash (High) if you want the stronger benchmark profile. Claude 3.5 Sonnet only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 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
DeepSeek V4 Flash (High) is clearly ahead on the BenchAlign aggregate, 53.95 to 47.74. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Flash (High)'s sharpest advantage is in mathematics, where it averages 91.9 against 1.6. The single biggest benchmark swing on the page is SWE-bench Verified, 49% to 78.6%. Claude 3.5 Sonnet does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude 3.5 Sonnet is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (High). That is roughly 53.6x on output cost alone. DeepSeek V4 Flash (High) is the reasoning model in the pair, while Claude 3.5 Sonnet 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. DeepSeek V4 Flash (High) gives you the larger context window at 1M, compared with 200K for Claude 3.5 Sonnet.
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 3.5 Sonnet | Δ | DeepSeek V4 Flash (High) |
|---|---|---|---|
| Math | Claude 3.5 Sonnet1.6 | Margin→ 90.3 | DeepSeek V4 Flash (High)91.9 |
| Coding | Claude 3.5 Sonnet49.0 | Margin→ 19.5 | DeepSeek V4 Flash (High)68.5 |
| Knowledge | Claude 3.5 Sonnet59.4 | Margin← 7.3 | DeepSeek V4 Flash (High)52.1 |
| Agentic | Claude 3.5 SonnetNot measured | MarginNo overlap | DeepSeek V4 Flash (High)55.3 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 49%B 78.6%Winner: DeepSeek V4 Flash (High)Δ 29.6SWE-bench Verified: Claude 3.5 Sonnet scored 49%; DeepSeek V4 Flash (High) scored 78.6%. DeepSeek V4 Flash (High) wins this benchmark. - Source ↗
GPQA
KnowledgeA 59.4%B 87.4%Winner: DeepSeek V4 Flash (High)Δ 28GPQA: Claude 3.5 Sonnet scored 59.4%; DeepSeek V4 Flash (High) scored 87.4%. DeepSeek V4 Flash (High) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude 3.5 Sonnet | DeepSeek V4 Flash (High) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude 3.5 Sonnet$3 input / $15 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 3.5 SonnetNot available | DeepSeek V4 Flash (High)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude 3.5 SonnetNot available | DeepSeek V4 Flash (High)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude 3.5 Sonnet200K | DeepSeek V4 Flash (High)1M | DeepSeek V4 Flash (High) lists the larger context window. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | Claude 3.5 Sonnet | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 56.6% | Not comparable |
| BrowseCompSource | — | 53.5% | Not comparable |
| HLE w/ toolsSource | — | 40.3% | Not comparable |
| MCP AtlasSource | — | 67.4% | Not comparable |
| ToolathlonSource | — | 43.5% | Not comparable |
| τ²-bench resultsSource | — | 95.6% | Not comparable |
| AA Agentic IndexSource | — | 28.2% | Not comparable |
| GDPval-AASource | — | 32.4% | Not comparable |
| GDPval-AASource | — | 1147 | Not comparable |
CodingDeepSeek V4 Flash (High) wins7 benchmarks
| Benchmark | Claude 3.5 Sonnet | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 49% | 78.6% | DeepSeek V4 Flash (High) leads |
| CodeforcesSource | — | 2816.0 | Not comparable |
| SWE-bench ProSource | — | 52.3% | Not comparable |
| SWE MultilingualSource | — | 70.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 56.6% | Not comparable |
| AA-SciCodeSource | — | 42.0% | Not comparable |
| AA Coding IndexSource | — | 52.0% | Not comparable |
Reasoning4 benchmarks
KnowledgeClaude 3.5 Sonnet wins12 benchmarks
| Benchmark | Claude 3.5 Sonnet | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| GPQASource | 59.4% | 87.4% | DeepSeek V4 Flash (High) leads |
| MMLU-ProSource | — | 86.4% | Not comparable |
| SimpleQASource | — | 28.9% | Not comparable |
| Chinese-SimpleQASource | — | 73.2% | Not comparable |
| GPQA-DSource | — | 87.4% | Not comparable |
| HLESource | — | 29.4% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 37.5% | Not comparable |
| AA-GPQA DiamondSource | — | 86.7% | Not comparable |
| AA-HLESource | — | 27.8% | Not comparable |
| AA-Omniscience IndexSource | — | -22.3% | Not comparable |
| AA-Omniscience AccuracySource | — | 35.5% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 89.7% | Not comparable |
MathDeepSeek V4 Flash (High) wins6 benchmarks
| Benchmark | Claude 3.5 Sonnet | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 2.069% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 0.000% | — | Not comparable |
| HMMT Feb 2026Source | — | 91.9% | Not comparable |
| IMOAnswerBenchSource | — | 85.1% | Not comparable |
| ApexSource | — | 19.1% | Not comparable |
| Apex ShortlistSource | — | 72.1% | Not comparable |
Multimodal1 benchmarks
| Benchmark | Claude 3.5 Sonnet | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1238 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Claude 3.5 Sonnet | DeepSeek V4 Flash (High) | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 73.5% | Not comparable |
Frequently Asked Questions (4)
Which is better, Claude 3.5 Sonnet or DeepSeek V4 Flash (High)?
DeepSeek V4 Flash (High) is ahead on BenchLM's BenchAlign leaderboard, 53.95 to 47.74. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 49% and 78.6%.
Which is better for knowledge tasks, Claude 3.5 Sonnet or DeepSeek V4 Flash (High)?
Claude 3.5 Sonnet has the edge for knowledge tasks in this comparison, averaging 59.4 versus 52.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, Claude 3.5 Sonnet or DeepSeek V4 Flash (High)?
DeepSeek V4 Flash (High) has the edge for coding in this comparison, averaging 68.5 versus 49. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, Claude 3.5 Sonnet or DeepSeek V4 Flash (High)?
DeepSeek V4 Flash (High) has the edge for math in this comparison, averaging 91.9 versus 1.6. Claude 3.5 Sonnet stays close enough that the answer can still flip depending on your workload.
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