# DeepSeek-V3.1-Terminus vs Sonar

> DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 38.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-terminus-vs-sonar
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.0 to 52.6.
- DeepSeek-V3.1-Terminus is cheaper at $0.27 / $1 per million input/output tokens, against $1 / $1 for Sonar.
- DeepSeek-V3.1-Terminus accepts more context: 164K tokens versus 128K.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.1-Terminus | Sonar |
|---|---|---|
| Provider | DeepSeek | Perplexity |
| Noometry Index | 43.1 | 38.5 |
| Rank | 97 | 187 |
| Context | 164K | 128K |
| Input $/M | $0.27 | $1 |
| Output $/M | $1 | $1 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.1-Terminus: 42.0 (#113)
- Sonar: 35.7 (#221)

| Benchmark | DeepSeek-V3.1-Terminus | Sonar |
|---|---|---|
| SciCode | 40.6% | — |
| LiveBench Coding | — | 35.1% |
| LMArena Coding | 1426 | — |
| ALE-Bench | 745.17 | — |

## Reasoning

- DeepSeek-V3.1-Terminus: 26.4 (#133)
- Sonar: 21.1 (#227)

| Benchmark | DeepSeek-V3.1-Terminus | Sonar |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| LiveBench Reasoning | — | 46.3% |
| LMArena Hard Prompts | 1426 | — |
| DTBench | 81.3% | — |
| LiveBench Data Analysis | — | 37.9% |
| LMCA | 28.6% | — |
| LiveBench | — | 46.9% |

## Math

- DeepSeek-V3.1-Terminus: 38.5 (#137)
- Sonar: 33.7 (#200)

| Benchmark | DeepSeek-V3.1-Terminus | Sonar |
|---|---|---|
| LiveBench Math | — | 41.6% |
| LMArena Math | 1402 | — |

## Multilingual

- DeepSeek-V3.1-Terminus: 52.1 (#92)
- Sonar: —

| Benchmark | DeepSeek-V3.1-Terminus | Sonar |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1436 | — |

## Instruction Following

- DeepSeek-V3.1-Terminus: 74.0 (#106)
- Sonar: 71.4 (#150)

| Benchmark | DeepSeek-V3.1-Terminus | Sonar |
|---|---|---|
| LiveBench Instruction Following | — | 76.2% |
| LMArena Instruction Following | 1404 | — |

## Long Context

- DeepSeek-V3.1-Terminus: 43.4 (#97)
- Sonar: —

| Benchmark | DeepSeek-V3.1-Terminus | Sonar |
|---|---|---|
| LMArena Longer Query | 1421 | — |

## Writing & Preference

- DeepSeek-V3.1-Terminus: 61.0 (#92)
- Sonar: 52.6 (#167)

| Benchmark | DeepSeek-V3.1-Terminus | Sonar |
|---|---|---|
| LMArena Text | 1419 | — |
| LMArena Creative Writing | 1403 | — |
| LMArena Multi-Turn | 1411 | — |
| LiveBench Language | — | 44.1% |

## FAQ

### Is DeepSeek-V3.1-Terminus better than Sonar?

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 38.5 on the Noometry Index.

### Which is cheaper, DeepSeek-V3.1-Terminus or Sonar?

DeepSeek-V3.1-Terminus is cheaper. It lists at $0.27 per million input tokens and $1 per million output tokens; Sonar lists at $1 and $1.

### Is DeepSeek-V3.1-Terminus or Sonar better for coding?

DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 35.7 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-V3.1-Terminus does, with 164K tokens against 128K.

### How many benchmarks do DeepSeek-V3.1-Terminus and Sonar share?

0 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Sonar has 7.