# DeepSeek Coder 33B vs GPT-5.5

> GPT-5.5 has enough public results to be ranked (#9); DeepSeek Coder 33B does not yet, so treat this comparison as directional.

- Canonical page: https://noometry.com/compare/deepseek-coder-33b-vs-gpt-5-5
- Last updated: 2026-10-11
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. DeepSeek Coder 33B scores higher in 0 categories and GPT-5.5 in 1 category; one gap is clear of the uncertainty.
- The widest gap is in coding, where GPT-5.5 leads 58.2 to 38.0.
- DeepSeek Coder 33B has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 38.9 | 63.4 |
| Rank | — | 9 |
| Context | — | 1.05M |
| Input $/M | — | $5 |
| Output $/M | — | $30 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek Coder 33B: 38.0 (#184)
- GPT-5.5: 58.2 (#17)

| Benchmark | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| SWE-bench Verified | — | 80.6% |
| DeepSWE | — | 67% |
| FrontierCode | — | 43% |
| LMArena WebDev | — | 1513 |
| SciCode | — | 56.1% |
| GSO | — | 40.2% |
| WeirdML | — | 84.9% |
| BigCodeBench Instruct | 42% | — |
| LMArena Coding | — | 1494 |
| MirrorCode | — | 10% |
| BigCodeBench Complete | 51.1% | — |
| ALE-Bench | — | 1,943 |
| HumanEval+ | 75% | — |
| MBPP+ | 70.1% | — |

## Agentic & Tool Use

- DeepSeek Coder 33B: —
- GPT-5.5: 50.7 (#6)

| Benchmark | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| Terminal-Bench | — | 84.7% |
| APEX-Agents | — | 55.1% |
| OSWorld 2.0 | — | 13% |
| Remote Labor Index | — | 6.3% |
| τ²-bench Banking | — | 44.6% |
| DeepResearch Bench | — | 54% |
| PostTrainBench | — | 27.2% |
| ExploitBench | — | 47.4% |
| GBAEval | — | 53.2% |
| GDP.pdf | — | 26% |
| LMArena Search | — | 1242 |
| Vending-Bench 2 | — | 7,524 |

## Reasoning

- DeepSeek Coder 33B: —
- GPT-5.5: 72.8 (#11)

| Benchmark | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| Epoch Capabilities Index | 96.32 | 159.1 |
| ARC-AGI-2 | — | 85% |
| SimpleBench | — | 69% |
| Kagi LLM Benchmark | — | 88.8% |
| NYT Connections (extended) | — | 96.2% |
| ARC-AGI-1 | — | 95% |
| CritPt | — | 27.1% |
| Chess Puzzles | — | 54% |
| EBR-Bench | — | 34.3% |
| LMArena Hard Prompts | — | 1489 |
| Mystery Game Puzzles | — | 56% |
| DTBench | — | 96% |
| LMCA | — | 54.3% |
| Surface Evolver Bench | — | 88.1% |
| Bench to the Future 3 | — | 0.14 |
| ForecastBench | — | 60.6 |
| WinoGrande | 62% | — |

## Math

- DeepSeek Coder 33B: —
- GPT-5.5: 81.7 (#11)

| Benchmark | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 85.3% |
| FrontierMath Tier 4 | — | 72.5% |
| MathArena Final-Answer Competitions | — | 94.3% |
| OTIS Mock AIME 2024-2025 | — | 100% |
| ProofBench | — | 50% |
| LMArena Math | — | 1486 |
| FrontierMath (Feb 2025 set) | — | 51.7% |
| FrontierMath Erdős | — | 0% |
| FrontierMath Tier 4 (v1) | — | 35.4% |
| GSM8K | 35.4% | — |

## Knowledge

- DeepSeek Coder 33B: —
- GPT-5.5: 64.4 (#17)

| Benchmark | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| GPQA Diamond | — | 94% |
| SimpleQA Verified | — | 63% |
| Vectara Hallucination Rate | — | 9.3% |
| LMArena Expert | — | 1508 |
| ARC (AI2) Challenge | 42.2% | — |
| MMLU | 39.4% | — |

## Multimodal

- DeepSeek Coder 33B: —
- GPT-5.5: 46.9 (#12)

| Benchmark | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| LMArena Vision | — | 1297 |
| Blueprint-Bench 2 | — | 36.2% |
| Furniture Assembly | — | 44.2% |
| LMArena Document | — | 1486 |

## Multilingual

- DeepSeek Coder 33B: —
- GPT-5.5: 56.4 (#20)

| Benchmark | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| LMArena Non-English | — | 1467 |
| LMArena Chinese | — | 1533 |
| LMArena French | — | 1486 |
| LMArena German | — | 1480 |
| LMArena Japanese | — | 1498 |
| LMArena Korean | — | 1460 |
| LMArena Russian | — | 1473 |
| LMArena Spanish | — | 1468 |

## Instruction Following

- DeepSeek Coder 33B: —
- GPT-5.5: 77.5 (#18)

| Benchmark | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| LMArena Instruction Following | — | 1479 |

## Long Context

- DeepSeek Coder 33B: —
- GPT-5.5: 48.3 (#12)

| Benchmark | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| CL-bench Life | — | 22.2% |
| LMArena Longer Query | — | 1484 |

## Writing & Preference

- DeepSeek Coder 33B: —
- GPT-5.5: 72.7 (#13)

| Benchmark | DeepSeek Coder 33B | GPT-5.5 |
|---|---|---|
| LMArena Text | — | 1472 |
| LMArena Creative Writing | — | 1455 |
| EQ-Bench Creative Writing | — | 1844 |
| EQ-Bench 4 | — | 1315 |
| LMArena Multi-Turn | — | 1476 |

## FAQ

### Is DeepSeek Coder 33B better than GPT-5.5?

GPT-5.5 has enough public results to be ranked (#9); DeepSeek Coder 33B does not yet, so treat this comparison as directional.

### Is DeepSeek Coder 33B or GPT-5.5 better for coding?

GPT-5.5 scores higher on coding benchmarks: 58.2 versus 38.0 in the Noometry coding category.

### How many benchmarks do DeepSeek Coder 33B and GPT-5.5 share?

1 benchmark has published results for both models. DeepSeek Coder 33B has 9 scored results on Noometry and GPT-5.5 has 71.