Model comparison
Claude Sonnet 5.5 vs DeepSeek-V3.2-Exp
Claude Sonnet 5.5 is the stronger model overall, scoring 61.9 to 44.3 on the Noometry Index. DeepSeek-V3.2-Exp costs 14× less per token, which makes it the better buy when Claude Sonnet 5.5's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
DeepSeekSummary
- They share 21 benchmarks with published results for both. Claude Sonnet 5.5 scores higher in 8 categories and DeepSeek-V3.2-Exp in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Sonnet 5.5 leads 87.9 to 41.7.
- The biggest single-benchmark swing is ProofBench: 100% for Claude Sonnet 5.5 and 8% for DeepSeek-V3.2-Exp.
- DeepSeek-V3.2-Exp is cheaper at $0.26 / $0.38 per million input/output tokens, against $2 / $10 for Claude Sonnet 5.5.
- Claude Sonnet 5.5 accepts more context: 1M tokens versus 164K.
- DeepSeek-V3.2-Exp has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 5.5 | DeepSeek-V3.2-Exp | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 61.9 | 44.3 |
| Released | 2026-09-28 | 2025-09-29 |
| Weights | Proprietary | Open |
| Context window | 1M | 164K |
| Max output | 128K | 66K |
| Input $ / M tokens | $2 | $0.26 |
| Output $ / M tokens | $10 | $0.38 |
| Results tracked | 32 | 49 |
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Category by category
Coding Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 67.3 (#6), DeepSeek-V3.2-Exp: 46.5 (#65)
| Benchmark | Claude Sonnet 5.5 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena WebDev | 1774 | 1362 |
| SciCode | 61% | 38.9% |
| LMArena Coding | 1513 | 1454 |
| FrontierCode | 52.1% | — |
| SWE-bench Verified (bash only) | — | 70% |
| Aider Polyglot | — | 74.2% |
| CursorBench | 55.5% | — |
| SWE-bench Multilingual | — | 59% |
| FrontierSWE | 61.9% | — |
| WeirdML | — | 39.5% |
| ALE-Bench | 1,819 | — |
Agentic & Tool Use Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 45.0 (#16), DeepSeek-V3.2-Exp: 32.7 (#59)
| Benchmark | Claude Sonnet 5.5 | DeepSeek-V3.2-Exp |
|---|---|---|
| APEX-Agents | 75.5% | 21.3% |
| Terminal-Bench | — | 39.6% |
| Berkeley Function Calling Leaderboard | — | 56.7% |
| TheAgentCompany | — | 42.9% |
| Vending-Bench 2 | — | 1,034 |
Reasoning Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 54.0 (#28), DeepSeek-V3.2-Exp: 22.1 (#208)
| Benchmark | Claude Sonnet 5.5 | DeepSeek-V3.2-Exp |
|---|---|---|
| NYT Connections (extended) | 80.5% | 36.7% |
| CritPt | 31.4% | 2.9% |
| LMArena Hard Prompts | 1495 | 1434 |
| Epoch Capabilities Index | 165.03 | 146.27 |
| ARC-AGI-2 | — | 4% |
| Kagi LLM Benchmark | — | 52.2% |
| ARC-AGI-1 | — | 57% |
| Chess Puzzles | — | 14% |
| Thematic Generalization | — | 65% |
| Mystery Game Puzzles | 65% | — |
| DTBench | — | 87.7% |
| LMCA | — | 29.1% |
Math Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 87.9 (#6), DeepSeek-V3.2-Exp: 41.7 (#87)
| Benchmark | Claude Sonnet 5.5 | DeepSeek-V3.2-Exp |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 87.8% |
| ProofBench | 100% | 8% |
| LMArena Math | 1510 | 1435 |
| FrontierMath (Tiers 1-3) | 88.8% | — |
| FrontierMath Tier 4 | 80.5% | — |
| MathArena Final-Answer Competitions | — | 57.7% |
| FrontierMath (Feb 2025 set) | — | 22.1% |
| FrontierMath Erdős | 2.9% | — |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 66.0 (#12), DeepSeek-V3.2-Exp: 51.7 (#66)
| Benchmark | Claude Sonnet 5.5 | DeepSeek-V3.2-Exp |
|---|---|---|
| GPQA Diamond | 95.6% | 83.4% |
| LMArena Expert | 1540 | 1436 |
| SimpleQA Verified | 46.5% | — |
| Vectara Hallucination Rate | — | 5.3% |
Multimodal Not comparable
Claude Sonnet 5.5: 51.5 (#6), DeepSeek-V3.2-Exp: —
| Benchmark | Claude Sonnet 5.5 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Vision | 1289 | — |
| Furniture Assembly | 75% | — |
Multilingual Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 55.3 (#30), DeepSeek-V3.2-Exp: 52.2 (#90)
| Benchmark | Claude Sonnet 5.5 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Non-English | 1452 | 1409 |
| LMArena Chinese | 1522 | 1461 |
| LMArena Russian | 1451 | 1424 |
| LMArena French | — | 1433 |
| LMArena German | — | 1440 |
| LMArena Japanese | — | 1374 |
| LMArena Korean | — | 1371 |
| LMArena Spanish | — | 1440 |
Instruction Following Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 78.3 (#11), DeepSeek-V3.2-Exp: 74.5 (#93)
| Benchmark | Claude Sonnet 5.5 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Instruction Following | 1495 | 1413 |
Long Context DeepSeek-V3.2-Exp leads
Claude Sonnet 5.5: 45.9 (#28), DeepSeek-V3.2-Exp: 47.6 (#16)
| Benchmark | Claude Sonnet 5.5 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Longer Query | 1498 | 1428 |
| Fiction.LiveBench | — | 83.3% |
| CL-bench | — | 13.2% |
| CL-bench Life | — | 9.5% |
Writing & Preference Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 66.0 (#40), DeepSeek-V3.2-Exp: 62.4 (#77)
| Benchmark | Claude Sonnet 5.5 | DeepSeek-V3.2-Exp |
|---|---|---|
| LMArena Text | 1471 | 1425 |
| LMArena Creative Writing | 1465 | 1403 |
| LMArena Multi-Turn | 1474 | 1427 |
| EQ-Bench Creative Writing | — | 1515 |
Frequently asked questions
Is Claude Sonnet 5.5 better than DeepSeek-V3.2-Exp?
Claude Sonnet 5.5 is the stronger model overall, scoring 61.9 to 44.3 on the Noometry Index. DeepSeek-V3.2-Exp costs 14× less per token, which makes it the better buy when Claude Sonnet 5.5's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 5.5 or DeepSeek-V3.2-Exp?
DeepSeek-V3.2-Exp is cheaper. It lists at $0.26 per million input tokens and $0.38 per million output tokens; Claude Sonnet 5.5 lists at $2 and $10.
Is Claude Sonnet 5.5 or DeepSeek-V3.2-Exp better for coding?
Claude Sonnet 5.5 scores higher on coding benchmarks: 67.3 versus 46.5 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 5.5 does, with 1M tokens against 164K.
How many benchmarks do Claude Sonnet 5.5 and DeepSeek-V3.2-Exp share?
21 benchmarks have published results for both models. Claude Sonnet 5.5 has 32 scored results on Noometry and DeepSeek-V3.2-Exp has 49.