# DeepSeek-V3.1-Terminus vs Grok 4.5

> Grok 4.5 is the stronger model overall, scoring 55.0 to 43.1 on the Noometry Index. DeepSeek-V3.1-Terminus costs 6.6× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-terminus-vs-grok-4-5
- Last updated: 2026-10-12
- Shared benchmarks: 16

## Summary

- They share 16 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 0 categories and Grok 4.5 in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.5 leads 56.1 to 26.4.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 57.4% for DeepSeek-V3.1-Terminus and 83.5% for Grok 4.5.
- DeepSeek-V3.1-Terminus is cheaper at $0.27 / $1 per million input/output tokens, against $2 / $6 for Grok 4.5.
- Grok 4.5 accepts more context: 500K tokens versus 164K.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| Provider | DeepSeek | xAI |
| Noometry Index | 43.1 | 55.0 |
| Rank | 97 | 25 |
| Context | 164K | 500K |
| Input $/M | $0.27 | $2 |
| Output $/M | $1 | $6 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.1-Terminus: 42.0 (#113)
- Grok 4.5: 52.2 (#35)

| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| SciCode | 40.6% | 54.1% |
| LMArena Coding | 1426 | 1474 |
| ALE-Bench | 745.17 | 1,309 |
| DeepSWE | — | 53.8% |
| FrontierCode | — | 42.4% |
| LMArena WebDev | — | 1553 |
| WeirdML | — | 46.4% |

## Agentic & Tool Use

- DeepSeek-V3.1-Terminus: —
- Grok 4.5: 44.4 (#17)

| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| APEX-Agents | — | 56.2% |
| τ²-bench Banking | — | 47.9% |
| PostTrainBench | — | 23.4% |
| GBAEval | — | 65.4% |
| GDP.pdf | — | 14% |
| LMArena Search | — | 1213 |
| Vending-Bench 2 | — | 3,887 |

## Reasoning

- DeepSeek-V3.1-Terminus: 26.4 (#133)
- Grok 4.5: 56.1 (#25)

| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | 83.5% |
| CritPt | 1.7% | 15.4% |
| LMArena Hard Prompts | 1426 | 1462 |
| DTBench | 81.3% | 96.5% |
| LMCA | 28.6% | 45.2% |
| ARC-AGI-2 | — | 52.6% |
| SimpleBench | — | 70% |
| NYT Connections (extended) | — | 79.9% |
| ARC-AGI-1 | — | 87.2% |
| Chess Puzzles | — | 36% |
| Surface Evolver Bench | — | 74.4% |
| Epoch Capabilities Index | — | 153.92 |

## Math

- DeepSeek-V3.1-Terminus: 38.5 (#137)
- Grok 4.5: 60.9 (#35)

| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Math | 1402 | 1459 |
| FrontierMath (Tiers 1-3) | — | 57.2% |
| FrontierMath Tier 4 | — | 24.4% |
| OTIS Mock AIME 2024-2025 | — | 97.8% |
| ProofBench | — | 31% |

## Knowledge

- DeepSeek-V3.1-Terminus: —
- Grok 4.5: 62.3 (#24)

| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| GPQA Diamond | — | 93.4% |
| SimpleQA Verified | — | 48.3% |
| LMArena Expert | — | 1466 |

## Multimodal

- DeepSeek-V3.1-Terminus: —
- Grok 4.5: 37.6 (#72)

| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Vision | — | 1288 |
| Blueprint-Bench 2 | — | 27.3% |
| Furniture Assembly | — | 22.5% |
| LMArena Document | — | 1452 |

## Multilingual

- DeepSeek-V3.1-Terminus: 52.1 (#92)
- Grok 4.5: 54.4 (#42)

| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Non-English | 1407 | 1440 |
| LMArena Russian | 1436 | 1448 |
| LMArena Chinese | — | 1496 |
| LMArena French | — | 1456 |
| LMArena German | — | 1446 |
| LMArena Japanese | — | 1428 |
| LMArena Korean | — | 1404 |
| LMArena Spanish | — | 1450 |

## Instruction Following

- DeepSeek-V3.1-Terminus: 74.0 (#106)
- Grok 4.5: 76.0 (#48)

| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Instruction Following | 1404 | 1446 |

## Long Context

- DeepSeek-V3.1-Terminus: 43.4 (#97)
- Grok 4.5: 44.8 (#56)

| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Longer Query | 1421 | 1463 |

## Writing & Preference

- DeepSeek-V3.1-Terminus: 61.0 (#92)
- Grok 4.5: 65.8 (#42)

| Benchmark | DeepSeek-V3.1-Terminus | Grok 4.5 |
|---|---|---|
| LMArena Text | 1419 | 1448 |
| LMArena Creative Writing | 1403 | 1442 |
| LMArena Multi-Turn | 1411 | 1456 |
| EQ-Bench Creative Writing | — | 1579 |

## FAQ

### Is DeepSeek-V3.1-Terminus better than Grok 4.5?

Grok 4.5 is the stronger model overall, scoring 55.0 to 43.1 on the Noometry Index. DeepSeek-V3.1-Terminus costs 6.6× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek-V3.1-Terminus or Grok 4.5?

DeepSeek-V3.1-Terminus is cheaper. It lists at $0.27 per million input tokens and $1 per million output tokens; Grok 4.5 lists at $2 and $6.

### Is DeepSeek-V3.1-Terminus or Grok 4.5 better for coding?

Grok 4.5 scores higher on coding benchmarks: 52.2 versus 42.0 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.5 does, with 500K tokens against 164K.

### How many benchmarks do DeepSeek-V3.1-Terminus and Grok 4.5 share?

16 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Grok 4.5 has 52.