Claude Sonnet 5.5 vs DeepSeek V3.2 Exp
Claude Sonnet 5.5 leads DeepSeek V3.2 Exp on the Artificial Analysis Intelligence Index, 56.0 to 16.6, and DeepSeek V3.2 Exp costs 24.4x less per output token ($0.41 vs $10.00 per million). Updated October 22, 2026; 38 benchmarks have a result for both.
vs boards won of 38 shared
Claude Sonnet 5.5 or DeepSeek V3.2 Exp: which to pick
Only Claude Sonnet 5.5 has a coding score, 87.3 on the Vibe Coding Index; DeepSeek V3.2 Exp has none, so the two cannot be ranked on coding.
Pick DeepSeek V3.2 Exp for output tokens 24.4x cheaper ($0.41 vs $10.00 per million) and work measured by LMArena Text: medicine and healthcare, where it leads.
Model AClaude Sonnet 5.5Anthropic87.3/1005 independent benchmarksNo cost per solved taskModel BDeepSeek V3.2 ExpDeepSeekNot benchmarked1 independent benchmarkNo cost per solved task
- Shared results
- 38
- Claude Sonnet 5.5 only
- 58
- DeepSeek V3.2 Exp only
- 21
- Like-for-like categories
- 7 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Claude Sonnet 5.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Claude Sonnet 5.5
Claude Sonnet 5.5 leads, 56.0 against 16.6.
Same board, both measured
Web design
Design Arena: websites
Claude Sonnet 5.5
Claude Sonnet 5.5 leads, 1326 against 1178.
Same board, both measured
General
Vals Index
No call
Only Claude Sonnet 5.5 has a Vals Index result, 70.8%.
Directional only
Long documents
Listed context window
Claude Sonnet 5.5
Claude Sonnet 5.5 takes 1M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.2 Exp
Claude Sonnet 5.5 $0.0070, DeepSeek V3.2 Exp $0.0005 per turn.
List prices
At a glance
- Coding index
- Claude Sonnet 5.5 87.3 from 5 benchmarks, DeepSeek V3.2 Exp not benchmarked.
- Widest category
- Coding, 36.9 points apart on average over 4 shared benchmarks.
- Widest single gap
- LMArena WebDev: Claude Sonnet 5.5 1768 against DeepSeek V3.2 Exp 1272, 70.9 points apart on a 0 to 100 scale.
- Output price
- Claude Sonnet 5.5 $10.00 against DeepSeek V3.2 Exp $0.41 per million output tokens, 24.4x apart.
- Context window
- Claude Sonnet 5.5 takes 1M tokens, DeepSeek V3.2 Exp 164K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Claude Sonnet 5.5 | Bars | DeepSeek V3.2 Exp | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 3 | 1 | ||
| Web design | 6 | 0 | ||
| General | 16 | 0 | ||
| All shared boards | 37 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | Claude Sonnet 5.5 | DeepSeek V3.2 Exp | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 74.2% | Only DeepSeek V3.2 Exp measured |
| LiveBench coding | 94.7% | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena WebDev | 1768 | 1272 | Claude Sonnet 5.5 |
| Terminal-Bench 4 (Vals AI) | 64.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Vibe Code Bench (Vals AI) | 92.4% | Not measured | Only Claude Sonnet 5.5 measured |
| Code migration (Vals AI) | 69.8% | Not measured | Only Claude Sonnet 5.5 measured |
| ProgramBench (Vals AI) | 6.5% | Not measured | Only Claude Sonnet 5.5 measured |
| IOI (Vals AI) | 83.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 83.2% | Not measured | Only Claude Sonnet 5.5 measured |
| SWE-bench Multimodal (Vals AI) | 58.3% | Not measured | Only Claude Sonnet 5.5 measured |
| CyberBench (Vals AI) | 59.6% | Not measured | Only Claude Sonnet 5.5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 78.9% | Only DeepSeek V3.2 Exp measured |
| SciCode | 61.0% | Not measured | Only Claude Sonnet 5.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 31.1% | Only DeepSeek V3.2 Exp measured |
| FrontierCode | 52.1% | Not measured | Only Claude Sonnet 5.5 measured |
| FrontierSWE | 61.9% | Not measured | Only Claude Sonnet 5.5 measured |
| WeirdML | Not measured | 39.5% | Only DeepSeek V3.2 Exp measured |
| ALE-Bench | 1819.1 | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Text: coding | 1513 | 1438 | Claude Sonnet 5.5 |
| LMArena Text: software and IT | 1504 | 1438 | Claude Sonnet 5.5 |
| LMArena WebDev: React | 1817 | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena WebDev: HTML | 1741 | 1281 | Claude Sonnet 5.5 |
| LMArena WebDev: from an image | 1737 | Not measured | Only Claude Sonnet 5.5 measured |
| SciCode | 13.8% | Not measured | Only Claude Sonnet 5.5 measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Sonnet 5.5 | DeepSeek V3.2 Exp | Leader |
|---|---|---|---|
| AA Intelligence Index | 56.0 | 16.6 | Claude Sonnet 5.5 |
| Epoch Capabilities Index | 166.2 | 144.9 | Claude Sonnet 5.5 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | Claude Sonnet 5.5 | DeepSeek V3.2 Exp | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1305 | Not measured | Only Claude Sonnet 5.5 measured |
| Design Arena: agents building mobile apps | 1260 | Not measured | Only Claude Sonnet 5.5 measured |
| Design Arena: spreadsheets | 1260 | Not measured | Only Claude Sonnet 5.5 measured |
| LiveBench research | 83.6% | Not measured | Only Claude Sonnet 5.5 measured |
| LiveBench browser | 84.0% | Not measured | Only Claude Sonnet 5.5 measured |
| LiveBench long agentic | 78.8% | Not measured | Only Claude Sonnet 5.5 measured |
| SREBench (Vals AI) | 30.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Finance Agent (Vals AI) | 58.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Tax Agent Bench (Vals AI) | 42.0% | Not measured | Only Claude Sonnet 5.5 measured |
| Legal Research Bench (Vals AI) | 48.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 10.4% | Not measured | Only Claude Sonnet 5.5 measured |
| Excel Modeling Benchmark (Vals AI) | 75.7% | Not measured | Only Claude Sonnet 5.5 measured |
| BioMysteryBench (Vals AI) | 81.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Terminal-Bench-Science (Vals AI) | 47.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Vals Science Index | 59.1% | Not measured | Only Claude Sonnet 5.5 measured |
| τ²-Bench Telecom | Not measured | 33.9% | Only DeepSeek V3.2 Exp measured |
| APEX-Agents | 75.5% | Not measured | Only Claude Sonnet 5.5 measured |
| TheAgentCompany | Not measured | 42.9% | Only DeepSeek V3.2 Exp measured |
| SpireClimb | 1.3% | Not measured | Only Claude Sonnet 5.5 measured |
| Vending-Bench 2 | $11,165 | Not measured | Only Claude Sonnet 5.5 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 56.7% | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 20 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Claude Sonnet 5.5 | DeepSeek V3.2 Exp | Leader |
|---|---|---|---|
| LiveBench reasoning | 91.6% | Not measured | Only Claude Sonnet 5.5 measured |
| MysteryMechanism (Vals AI) | 49.1% | Not measured | Only Claude Sonnet 5.5 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 79.7% | Only DeepSeek V3.2 Exp measured |
| Humanity's Last Exam (Artificial Analysis run) | 55.0% | 14.9% | Claude Sonnet 5.5 |
| GPQA Diamond (Epoch AI run) | 95.6% | Not measured | Only Claude Sonnet 5.5 measured |
| Chess puzzles | 59.0% | Not measured | Only Claude Sonnet 5.5 measured |
| Mystery game puzzles | 65.0% | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Text: hard prompts | 1494 | 1429 | Claude Sonnet 5.5 |
| LMArena Text: expert | 1531 | 1422 | Claude Sonnet 5.5 |
| LMArena Text: hard prompts in English | 1502 | 1444 | Claude Sonnet 5.5 |
| LMArena Vision: diagrams | 1329 | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Vision: homework | 1331 | Not measured | Only Claude Sonnet 5.5 measured |
| Kagi LLM Benchmark | Not measured | 52.2% | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Sonnet 5.5 | DeepSeek V3.2 Exp | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 87.7 | Only DeepSeek V3.2 Exp measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 87.7% | Only DeepSeek V3.2 Exp measured |
| OTIS Mock AIME | 100.0% | Not measured | Only Claude Sonnet 5.5 measured |
| FrontierMath, tiers 1 to 3 | 88.8% | Not measured | Only Claude Sonnet 5.5 measured |
| FrontierMath, tier 4 | 80.5% | Not measured | Only Claude Sonnet 5.5 measured |
| ProofBench | 100.0% | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Text: math | 1497 | 1422 | Claude Sonnet 5.5 |
| LMArena Text: mathematical work | 1510 | 1433 | Claude Sonnet 5.5 |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | Claude Sonnet 5.5 | DeepSeek V3.2 Exp | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 52.9% | Not measured | Only Claude Sonnet 5.5 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 85.0% | Only DeepSeek V3.2 Exp measured |
| SimpleQA Verified | 46.5% | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Text: science | 1483 | 1443 | Claude Sonnet 5.5 |
| LMArena Text: medicine and healthcare | 1464 | 1468 | DeepSeek V3.2 Exp |
| LMArena Text: legal and government | 1483 | 1419 | Claude Sonnet 5.5 |
| LMArena Text: business and finance | 1468 | 1412 | Claude Sonnet 5.5 |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Sonnet 5.5 | DeepSeek V3.2 Exp | Leader |
|---|---|---|---|
| Design Arena: websites | 1326 | 1178 | Claude Sonnet 5.5 |
| Design Arena: UI components | 1368 | 1164 | Claude Sonnet 5.5 |
| Design Arena: game dev | 1471 | 1144 | Claude Sonnet 5.5 |
| Design Arena: data viz | 1392 | 1152 | Claude Sonnet 5.5 |
| Design Arena: 3D | 1445 | 1148 | Claude Sonnet 5.5 |
| Design Arena: all code categories | 1364 | 1170 | Claude Sonnet 5.5 |
| Design Arena: SVG | Not measured | 1031 | Only DeepSeek V3.2 Exp measured |
| LiveBench design | 85.0% | Not measured | Only Claude Sonnet 5.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index160
| Benchmark | Claude Sonnet 5.5 | DeepSeek V3.2 Exp | Leader |
|---|---|---|---|
| Vals Index | 70.8% | Not measured | Only Claude Sonnet 5.5 measured |
| LiveBench data analysis | 59.5% | Not measured | Only Claude Sonnet 5.5 measured |
| Public Benefits Bench (Vals AI) | 67.2% | Not measured | Only Claude Sonnet 5.5 measured |
| SAGE (Vals AI) | 51.8% | Not measured | Only Claude Sonnet 5.5 measured |
| MedScribe (Vals AI) | 91.1% | Not measured | Only Claude Sonnet 5.5 measured |
| IFBench | Not measured | 54.1% | Only DeepSeek V3.2 Exp measured |
| Long context reasoning (AA-LCR) | 82.7% | 72.3% | Claude Sonnet 5.5 |
| DTBench | 97.3% | 87.7% | Claude Sonnet 5.5 |
| LMCA | 68.3% | 29.1% | Claude Sonnet 5.5 |
| Fiction.LiveBench | Not measured | 83.3% | Only DeepSeek V3.2 Exp measured |
| CL-bench | Not measured | 13.2% | Only DeepSeek V3.2 Exp measured |
| Furniture assembly | 75.0% | Not measured | Only Claude Sonnet 5.5 measured |
| CL-bench Life | Not measured | 9.5% | Only DeepSeek V3.2 Exp measured |
| LMArena Text | 1473 | 1425 | Claude Sonnet 5.5 |
| LMArena Text: instruction following | 1492 | 1401 | Claude Sonnet 5.5 |
| LMArena Text: creative writing | 1467 | 1404 | Claude Sonnet 5.5 |
| LMArena Vision | 1287 | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Text: English | 1484 | 1441 | Claude Sonnet 5.5 |
| LMArena Text: non-English | 1456 | 1404 | Claude Sonnet 5.5 |
| LMArena Text: Chinese | 1535 | 1461 | Claude Sonnet 5.5 |
| LMArena Text: German | Not measured | 1440 | Only DeepSeek V3.2 Exp measured |
| LMArena Text: Japanese | Not measured | 1331 | Only DeepSeek V3.2 Exp measured |
| LMArena Text: Korean | Not measured | 1372 | Only DeepSeek V3.2 Exp measured |
| LMArena Text: French | 1499 | 1434 | Claude Sonnet 5.5 |
| LMArena Text: Spanish | 1451 | 1441 | Claude Sonnet 5.5 |
| LMArena Text: Russian | 1454 | 1412 | Claude Sonnet 5.5 |
| LMArena Text: Polish | Not measured | 1435 | Only DeepSeek V3.2 Exp measured |
| LMArena Text: multi-turn | 1465 | 1422 | Claude Sonnet 5.5 |
| LMArena Text: longer queries | 1495 | 1418 | Claude Sonnet 5.5 |
| LMArena Text: writing and language | 1474 | 1407 | Claude Sonnet 5.5 |
| LMArena Text: entertainment and media | 1461 | 1407 | Claude Sonnet 5.5 |
| LMArena Vision: English | 1289 | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Vision: reading text | 1297 | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Vision: creative writing | 1242 | Not measured | Only Claude Sonnet 5.5 measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Sonnet 5.5 | DeepSeek V3.2 Exp | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Claude Sonnet 5.5$0.0070Fits in one request
DeepSeek V3.2 Exp$0.0005Fits in one request
DeepSeek V3.2 Exp costs less
Repository review
50K input + 3K output tokens
Claude Sonnet 5.5$0.130Fits in one request
DeepSeek V3.2 Exp$0.015Fits in one request
DeepSeek V3.2 Exp costs less
Agent loop
200K input + 10K output tokens
Claude Sonnet 5.5$0.500Fits in one request
DeepSeek V3.2 Exp$0.058Exceeds the context window
DeepSeek V3.2 Exp costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Anthropic Claude Sonnet 5.5 | DeepSeek V3.2 Exp |
|---|---|---|
| Maker | Anthropic | DeepSeek |
| Weights | No public weights listed | Open weights |
| Released | September 28, 2026 | September 29, 2025 |
| Context window | 1M | 164K |
| Input $/Mtok | $2.00 | $0.27 |
| Output $/Mtok | $10.00 | $0.41 |
| Coding index | 87.3 | Not benchmarked |
| Independent measurements behind it | 5 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Sonnet 5.5 better than DeepSeek V3.2 Exp for coding?
Only Claude Sonnet 5.5 has a coding score, 87.3 on the Vibe Coding Index; DeepSeek V3.2 Exp has none, so the two cannot be ranked on coding. Pick DeepSeek V3.2 Exp for output tokens 24.4x cheaper ($0.41 vs $10.00 per million) and work measured by LMArena Text: medicine and healthcare, where it leads.
Which is cheaper, Claude Sonnet 5.5 or DeepSeek V3.2 Exp?
Claude Sonnet 5.5 costs $2.00 per million input tokens and $10.00 per million output tokens; DeepSeek V3.2 Exp costs $0.27 and $0.41. Cost per solved task is known for neither of them.
Which has the bigger context window, Claude Sonnet 5.5 or DeepSeek V3.2 Exp?
Claude Sonnet 5.5, with 1M tokens against 164K.
How many benchmarks is the Claude Sonnet 5.5 vs DeepSeek V3.2 Exp comparison based on?
38 benchmarks have a result for both models as of October 22, 2026. Claude Sonnet 5.5's coding index rests on 5 independent benchmarks and DeepSeek V3.2 Exp's on 1. Where only one model has a result, the page says so instead of naming a winner.