# DeepSeek-V3.1-Terminus vs Step 3.7 Flash

> DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 36.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-terminus-vs-step-3-7-flash
- Last updated: 2026-10-10
- Shared benchmarks: 3

## Summary

- They share 3 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 2 categories and Step 3.7 Flash in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where Step 3.7 Flash leads 40.9 to 35.7.
- Step 3.7 Flash is cheaper at $0.18 / $1.11 per million input/output tokens, against $0.30 / $1 for DeepSeek-V3.1-Terminus.
- Step 3.7 Flash accepts more context: 256K tokens versus 164K.

## Snapshot

| | DeepSeek-V3.1-Terminus | Step 3.7 Flash |
|---|---|---|
| Provider | DeepSeek | StepFun |
| Noometry Index | 42.6 | 36.5 |
| Rank | 96 | 207 |
| Context | 164K | 256K |
| Input $/M | $0.30 | $0.18 |
| Output $/M | $1 | $1.11 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1-Terminus: 41.5 (#114)
- Step 3.7 Flash: 39.4 (#147)

| Benchmark | DeepSeek-V3.1-Terminus | Step 3.7 Flash |
|---|---|---|
| SciCode | 40.6% | 40% |
| ALE-Bench | 745.17 | 694.12 |
| LMArena Coding | 1426 | — |

## Reasoning

- DeepSeek-V3.1-Terminus: 25.7 (#126)
- Step 3.7 Flash: 20.9 (#211)

| Benchmark | DeepSeek-V3.1-Terminus | Step 3.7 Flash |
|---|---|---|
| CritPt | 1.7% | 2.3% |
| Kagi LLM Benchmark | 57.4% | — |
| NYT Connections (extended) | — | 39.7% |
| LMArena Hard Prompts | 1427 | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |

## Math

- DeepSeek-V3.1-Terminus: 35.7 (#138)
- Step 3.7 Flash: 40.9 (#74)

| Benchmark | DeepSeek-V3.1-Terminus | Step 3.7 Flash |
|---|---|---|
| MathArena Final-Answer Competitions | — | 68.5% |
| LMArena Math | 1402 | — |

## Multilingual

- DeepSeek-V3.1-Terminus: 52.3 (#87)
- Step 3.7 Flash: —

| Benchmark | DeepSeek-V3.1-Terminus | Step 3.7 Flash |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1434 | — |

## Instruction Following

- DeepSeek-V3.1-Terminus: 74.4 (#96)
- Step 3.7 Flash: —

| Benchmark | DeepSeek-V3.1-Terminus | Step 3.7 Flash |
|---|---|---|
| LMArena Instruction Following | 1406 | — |

## Long Context

- DeepSeek-V3.1-Terminus: 43.5 (#88)
- Step 3.7 Flash: —

| Benchmark | DeepSeek-V3.1-Terminus | Step 3.7 Flash |
|---|---|---|
| LMArena Longer Query | 1426 | — |

## Writing & Preference

- DeepSeek-V3.1-Terminus: 61.3 (#87)
- Step 3.7 Flash: —

| Benchmark | DeepSeek-V3.1-Terminus | Step 3.7 Flash |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1404 | — |
| LMArena Multi-Turn | 1411 | — |

## FAQ

### Is DeepSeek-V3.1-Terminus better than Step 3.7 Flash?

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 36.5 on the Noometry Index.

### Which is cheaper, DeepSeek-V3.1-Terminus or Step 3.7 Flash?

Step 3.7 Flash is cheaper. It lists at $0.18 per million input tokens and $1.11 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.30 and $1.

### Is DeepSeek-V3.1-Terminus or Step 3.7 Flash better for coding?

DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 41.5 versus 39.4 in the Noometry coding category.

### Which has the bigger context window?

Step 3.7 Flash does, with 256K tokens against 164K.

### How many benchmarks do DeepSeek-V3.1-Terminus and Step 3.7 Flash share?

3 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Step 3.7 Flash has 5.