# DeepSeek V4 Pro vs Mercury 2

> DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 39.1 on the Noometry Index. Mercury 2 costs 2.6× less per token, which makes it the better buy when DeepSeek V4 Pro's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v4-pro-vs-mercury-2
- Last updated: 2026-10-11
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 7 categories and Mercury 2 in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Pro leads 56.5 to 23.8.
- The biggest single-benchmark swing is WeirdML: 66.2% for DeepSeek V4 Pro and 43.2% for Mercury 2.
- Mercury 2 is cheaper at $0.25 / $0.75 per million input/output tokens, against $0.66 / $1.98 for DeepSeek V4 Pro.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 128K.
- DeepSeek V4 Pro has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek V4 Pro | Mercury 2 |
|---|---|---|
| Provider | DeepSeek | Inception |
| Noometry Index | 54.3 | 39.1 |
| Rank | 31 | 175 |
| Context | 1M | 128K |
| Input $/M | $0.66 | $0.25 |
| Output $/M | $1.98 | $0.75 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek V4 Pro: 52.4 (#34)
- Mercury 2: 33.5 (#255)

| Benchmark | DeepSeek V4 Pro | Mercury 2 |
|---|---|---|
| LMArena WebDev | 1582 | 1171 |
| SciCode | 51% | 38.7% |
| WeirdML | 66.2% | 43.2% |
| LMArena Coding | 1470 | 1391 |
| ALE-Bench | 1,403 | 785.58 |
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |

## Agentic & Tool Use

- DeepSeek V4 Pro: 32.8 (#58)
- Mercury 2: —

| Benchmark | DeepSeek V4 Pro | Mercury 2 |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Vending-Bench 2 | 3,285 | — |

## Reasoning

- DeepSeek V4 Pro: 56.5 (#24)
- Mercury 2: 23.8 (#170)

| Benchmark | DeepSeek V4 Pro | Mercury 2 |
|---|---|---|
| CritPt | 18% | 0.8% |
| LMArena Hard Prompts | 1461 | 1362 |
| ARC-AGI-2 | 61.3% | — |
| Kagi LLM Benchmark | 53.5% | — |
| NYT Connections (extended) | 91.3% | — |
| ARC-AGI-1 | 90.5% | — |
| Chess Puzzles | 47% | — |
| Mystery Game Puzzles | 43% | — |
| DTBench | 93.9% | — |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| Epoch Capabilities Index | 155.31 | — |
| ForecastBench | 56.1 | — |

## Math

- DeepSeek V4 Pro: 64.8 (#30)
- Mercury 2: —

| Benchmark | DeepSeek V4 Pro | Mercury 2 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| OTIS Mock AIME 2024-2025 | 98.6% | — |
| ProofBench | 50% | — |
| LMArena Math | 1455 | — |

## Knowledge

- DeepSeek V4 Pro: 59.5 (#31)
- Mercury 2: 36.2 (#172)

| Benchmark | DeepSeek V4 Pro | Mercury 2 |
|---|---|---|
| Vectara Hallucination Rate | 8.6% | 12.3% |
| LMArena Expert | 1464 | 1358 |
| GPQA Diamond | 91.7% | — |
| SimpleQA Verified | 52.9% | — |

## Multilingual

- DeepSeek V4 Pro: 54.4 (#45)
- Mercury 2: 46.6 (#157)

| Benchmark | DeepSeek V4 Pro | Mercury 2 |
|---|---|---|
| LMArena Non-English | 1439 | 1331 |
| LMArena Chinese | 1486 | 1417 |
| LMArena Russian | 1453 | 1304 |
| LMArena French | 1472 | — |
| LMArena German | 1458 | — |
| LMArena Japanese | 1445 | — |
| LMArena Korean | 1447 | — |
| LMArena Spanish | 1458 | — |

## Instruction Following

- DeepSeek V4 Pro: 76.1 (#47)
- Mercury 2: 70.2 (#165)

| Benchmark | DeepSeek V4 Pro | Mercury 2 |
|---|---|---|
| LMArena Instruction Following | 1448 | 1329 |

## Long Context

- DeepSeek V4 Pro: 45.0 (#51)
- Mercury 2: 40.5 (#154)

| Benchmark | DeepSeek V4 Pro | Mercury 2 |
|---|---|---|
| LMArena Longer Query | 1458 | 1330 |
| CL-bench Life | 13.5% | — |

## Writing & Preference

- DeepSeek V4 Pro: 65.5 (#46)
- Mercury 2: 53.8 (#155)

| Benchmark | DeepSeek V4 Pro | Mercury 2 |
|---|---|---|
| LMArena Text | 1451 | 1355 |
| LMArena Creative Writing | 1446 | 1289 |
| LMArena Multi-Turn | 1467 | 1358 |
| EQ-Bench Creative Writing | 1553 | — |
| EQ-Bench 4 | 1166 | — |

## FAQ

### Is DeepSeek V4 Pro better than Mercury 2?

DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 39.1 on the Noometry Index. Mercury 2 costs 2.6× less per token, which makes it the better buy when DeepSeek V4 Pro's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek V4 Pro or Mercury 2?

Mercury 2 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; DeepSeek V4 Pro lists at $0.66 and $1.98.

### Is DeepSeek V4 Pro or Mercury 2 better for coding?

DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 33.5 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek V4 Pro does, with 1M tokens against 128K.

### How many benchmarks do DeepSeek V4 Pro and Mercury 2 share?

17 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Mercury 2 has 17.