Model comparison
Claude Opus 5.5 vs DeepSeek-V3.2-Speciale
Claude Opus 5.5 is the stronger model overall, scoring 68.6 to 39.7 on the Noometry Index. DeepSeek-V3.2-Speciale costs 9.4× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
DeepSeekSummary
- They share 1 benchmark with published results for both. Claude Opus 5.5 scores higher in 3 categories and DeepSeek-V3.2-Speciale in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 5.5 leads 80.2 to 32.9.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $4 / $20 for Claude Opus 5.5.
- Claude Opus 5.5 accepts more context: 1M tokens versus 128K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 5.5 | DeepSeek-V3.2-Speciale | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 68.6 | 39.7 |
| Released | 2026-09-22 | 2025-12-01 |
| Weights | Proprietary | Open |
| Context window | 1M | 128K |
| Max output | 128K | 128K |
| Input $ / M tokens | $4 | $0.58 |
| Output $ / M tokens | $20 | $1.68 |
| Results tracked | 44 | 3 |
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Category by category
Coding Claude Opus 5.5 leads
Claude Opus 5.5: 71.9 (#3), DeepSeek-V3.2-Speciale: 40.4 (#140)
| Benchmark | Claude Opus 5.5 | DeepSeek-V3.2-Speciale |
|---|---|---|
| FrontierCode | 54.6% | — |
| CursorBench | 57.8% | — |
| LMArena WebDev | 1813 | — |
| FrontierSWE | 62.3% | — |
| SciCode | 66.9% | — |
| WeirdML | — | 46.7% |
| LMArena Coding | 1547 | — |
| MirrorCode | 77.4% | — |
| ALE-Bench | 2,147 | — |
Agentic & Tool Use Not comparable
Claude Opus 5.5: 45.3 (#15), DeepSeek-V3.2-Speciale: —
| Benchmark | Claude Opus 5.5 | DeepSeek-V3.2-Speciale |
|---|---|---|
| APEX-Agents | 73.5% | — |
| GDP.pdf | 30.6% | — |
| Vending-Bench 2 | 9,235 | — |
Reasoning Claude Opus 5.5 leads
Claude Opus 5.5: 80.2 (#3), DeepSeek-V3.2-Speciale: 32.9 (#73)
| Benchmark | Claude Opus 5.5 | DeepSeek-V3.2-Speciale |
|---|---|---|
| ARC-AGI-2 | 93.3% | — |
| SimpleBench | — | 52.6% |
| NYT Connections (extended) | 88.5% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 31.7% | — |
| EBR-Bench | 71.4% | — |
| LMArena Hard Prompts | 1535 | — |
| Mystery Game Puzzles | 71% | — |
| DTBench | 98.9% | — |
| LMCA | 68.2% | — |
| Epoch Capabilities Index | 167.33 | — |
Math Not comparable
Claude Opus 5.5: 91.8 (#3), DeepSeek-V3.2-Speciale: —
| Benchmark | Claude Opus 5.5 | DeepSeek-V3.2-Speciale |
|---|---|---|
| FrontierMath (Tiers 1-3) | 91.2% | — |
| FrontierMath Tier 4 | 95% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 100% | — |
| LMArena Math | 1506 | — |
| FrontierMath Erdős | 2.9% | — |
Knowledge Not comparable
Claude Opus 5.5: 66.4 (#10), DeepSeek-V3.2-Speciale: —
| Benchmark | Claude Opus 5.5 | DeepSeek-V3.2-Speciale |
|---|---|---|
| GPQA Diamond | 90.6% | — |
| SimpleQA Verified | 72.2% | — |
| LMArena Expert | 1547 | — |
Multimodal Not comparable
Claude Opus 5.5: 57.8 (#1), DeepSeek-V3.2-Speciale: —
| Benchmark | Claude Opus 5.5 | DeepSeek-V3.2-Speciale |
|---|---|---|
| LMArena Vision | 1321 | — |
| Blueprint-Bench 2 | 51.2% | — |
| Furniture Assembly | 83.3% | — |
Multilingual Not comparable
Claude Opus 5.5: 59.1 (#2), DeepSeek-V3.2-Speciale: —
| Benchmark | Claude Opus 5.5 | DeepSeek-V3.2-Speciale |
|---|---|---|
| LMArena Non-English | 1507 | — |
| LMArena Chinese | 1588 | — |
| LMArena French | 1514 | — |
| LMArena Russian | 1520 | — |
| LMArena Spanish | 1507 | — |
Instruction Following Not comparable
Claude Opus 5.5: 80.0 (#3), DeepSeek-V3.2-Speciale: —
| Benchmark | Claude Opus 5.5 | DeepSeek-V3.2-Speciale |
|---|---|---|
| LMArena Instruction Following | 1537 | — |
Long Context Not comparable
Claude Opus 5.5: 47.1 (#19), DeepSeek-V3.2-Speciale: —
| Benchmark | Claude Opus 5.5 | DeepSeek-V3.2-Speciale |
|---|---|---|
| LMArena Longer Query | 1532 | — |
Writing & Preference Claude Opus 5.5 leads
Claude Opus 5.5: 78.2 (#3), DeepSeek-V3.2-Speciale: 46.0 (#222)
| Benchmark | Claude Opus 5.5 | DeepSeek-V3.2-Speciale |
|---|---|---|
| EQ-Bench Creative Writing | 2050 | 1276 |
| LMArena Text | 1515 | — |
| LMArena Creative Writing | 1533 | — |
| LMArena Multi-Turn | 1499 | — |
Frequently asked questions
Is Claude Opus 5.5 better than DeepSeek-V3.2-Speciale?
Claude Opus 5.5 is the stronger model overall, scoring 68.6 to 39.7 on the Noometry Index. DeepSeek-V3.2-Speciale costs 9.4× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 5.5 or DeepSeek-V3.2-Speciale?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Claude Opus 5.5 lists at $4 and $20.
Is Claude Opus 5.5 or DeepSeek-V3.2-Speciale better for coding?
Claude Opus 5.5 scores higher on coding benchmarks: 71.9 versus 40.4 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 5.5 does, with 1M tokens against 128K.
How many benchmarks do Claude Opus 5.5 and DeepSeek-V3.2-Speciale share?
1 benchmark has published results for both models. Claude Opus 5.5 has 44 scored results on Noometry and DeepSeek-V3.2-Speciale has 3.