# DeepSeek Coder 1.3B vs GPT-6.1 Sol

> GPT-6.1 Sol has enough public results to be ranked (#6); DeepSeek Coder 1.3B does not yet, so treat this comparison as directional.

- Canonical page: https://noometry.com/compare/deepseek-coder-1-3b-vs-gpt-6-1-sol
- Last updated: 2026-10-10
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. DeepSeek Coder 1.3B scores higher in 0 categories and GPT-6.1 Sol in 1 category; one gap is clear of the uncertainty.
- The widest gap is in coding, where GPT-6.1 Sol leads 63.2 to 31.2.
- DeepSeek Coder 1.3B has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 35.0 | 65.6 |
| Rank | — | 6 |
| Context | — | 1.05M |
| Input $/M | — | $2 |
| Output $/M | — | $10 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek Coder 1.3B: 31.2 (#287)
- GPT-6.1 Sol: 63.2 (#8)

| Benchmark | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| DeepSWE | — | 75.2% |
| FrontierCode | — | 50.2% |
| LMArena WebDev | — | 1755 |
| SciCode | — | 55.8% |
| BigCodeBench Instruct | 22.8% | — |
| LMArena Coding | — | 1487 |
| BigCodeBench Complete | 29.6% | — |
| HumanEval+ | 60.4% | — |
| MBPP+ | 54.8% | — |

## Agentic & Tool Use

- DeepSeek Coder 1.3B: —
- GPT-6.1 Sol: 39.6 (#26)

| Benchmark | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| APEX-Agents | — | 60% |
| GDP.pdf | — | 32% |

## Reasoning

- DeepSeek Coder 1.3B: —
- GPT-6.1 Sol: 81.9 (#2)

| Benchmark | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| Epoch Capabilities Index | 63.6 | 166.09 |
| ARC-AGI-2 | — | 94.2% |
| NYT Connections (extended) | — | 95.5% |
| ARC-AGI-1 | — | 98.5% |
| CritPt | — | 31.7% |
| Chess Puzzles | — | 61% |
| EBR-Bench | — | 54.3% |
| LMArena Hard Prompts | — | 1466 |
| Mystery Game Puzzles | — | 80% |
| WinoGrande | 53.3% | — |

## Math

- DeepSeek Coder 1.3B: —
- GPT-6.1 Sol: 93.7 (#1)

| Benchmark | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 93.7% |
| FrontierMath Tier 4 | — | 100% |
| OTIS Mock AIME 2024-2025 | — | 100% |
| ProofBench | — | 99% |
| LMArena Math | — | 1464 |
| GSM8K | 4.4% | — |

## Knowledge

- DeepSeek Coder 1.3B: —
- GPT-6.1 Sol: 71.8 (#4)

| Benchmark | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| GPQA Diamond | — | 95.4% |
| SimpleQA Verified | — | 73.9% |
| LMArena Expert | — | 1502 |
| ARC (AI2) Challenge | 25.4% | — |
| MMLU | 25.8% | — |

## Multimodal

- DeepSeek Coder 1.3B: —
- GPT-6.1 Sol: 52.7 (#5)

| Benchmark | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | — | 1288 |
| Furniture Assembly | — | 80% |

## Multilingual

- DeepSeek Coder 1.3B: —
- GPT-6.1 Sol: 54.3 (#46)

| Benchmark | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | — | 1438 |
| LMArena Chinese | — | 1477 |
| LMArena Russian | — | 1455 |

## Instruction Following

- DeepSeek Coder 1.3B: —
- GPT-6.1 Sol: 77.0 (#29)

| Benchmark | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| LMArena Instruction Following | — | 1468 |

## Long Context

- DeepSeek Coder 1.3B: —
- GPT-6.1 Sol: 44.9 (#54)

| Benchmark | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| LMArena Longer Query | — | 1465 |

## Writing & Preference

- DeepSeek Coder 1.3B: —
- GPT-6.1 Sol: 63.6 (#63)

| Benchmark | DeepSeek Coder 1.3B | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | — | 1447 |
| LMArena Creative Writing | — | 1432 |
| LMArena Multi-Turn | — | 1449 |

## FAQ

### Is DeepSeek Coder 1.3B better than GPT-6.1 Sol?

GPT-6.1 Sol has enough public results to be ranked (#6); DeepSeek Coder 1.3B does not yet, so treat this comparison as directional.

### Is DeepSeek Coder 1.3B or GPT-6.1 Sol better for coding?

GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 31.2 in the Noometry coding category.

### How many benchmarks do DeepSeek Coder 1.3B and GPT-6.1 Sol share?

1 benchmark has published results for both models. DeepSeek Coder 1.3B has 9 scored results on Noometry and GPT-6.1 Sol has 34.