# DeepSeek V4 Pro vs Qwen3-30B-A3B

> DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 38.9 on the Noometry Index. Qwen3-30B-A3B costs 4.6× 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-qwen3-30b-a3b
- Last updated: 2026-10-10
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 9 categories and Qwen3-30B-A3B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Pro leads 56.5 to 22.2.
- The biggest single-benchmark swing is Chess Puzzles: 47% for DeepSeek V4 Pro and 8% for Qwen3-30B-A3B.
- Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $0.66 / $1.98 for DeepSeek V4 Pro.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 41K.

## Snapshot

| | DeepSeek V4 Pro | Qwen3-30B-A3B |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 54.3 | 38.9 |
| Rank | 31 | 179 |
| Context | 1M | 41K |
| Input $/M | $0.66 | $0.12 |
| Output $/M | $1.98 | $0.50 |
| Weights | Open | Open |

## Coding

- DeepSeek V4 Pro: 52.4 (#34)
- Qwen3-30B-A3B: 37.5 (#194)

| Benchmark | DeepSeek V4 Pro | Qwen3-30B-A3B |
|---|---|---|
| SciCode | 51% | 33.3% |
| WeirdML | 66.2% | 29.8% |
| LMArena Coding | 1470 | 1416 |
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| LMArena WebDev | 1582 | — |
| ALE-Bench | 1,403 | — |

## Agentic & Tool Use

- DeepSeek V4 Pro: 32.8 (#58)
- Qwen3-30B-A3B: 29.8 (#82)

| Benchmark | DeepSeek V4 Pro | Qwen3-30B-A3B |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Berkeley Function Calling Leaderboard | — | 41.4% |
| Vending-Bench 2 | 3,285 | — |

## Reasoning

- DeepSeek V4 Pro: 56.5 (#24)
- Qwen3-30B-A3B: 22.2 (#204)

| Benchmark | DeepSeek V4 Pro | Qwen3-30B-A3B |
|---|---|---|
| Kagi LLM Benchmark | 53.5% | 54.9% |
| CritPt | 18% | 0.3% |
| Chess Puzzles | 47% | 8% |
| LMArena Hard Prompts | 1461 | 1398 |
| DTBench | 93.9% | 69.3% |
| LMCA | 45.5% | 22.4% |
| Epoch Capabilities Index | 155.31 | 139.63 |
| ARC-AGI-2 | 61.3% | — |
| NYT Connections (extended) | 91.3% | — |
| ARC-AGI-1 | 90.5% | — |
| Mystery Game Puzzles | 43% | — |
| Surface Evolver Bench | 40% | — |
| ForecastBench | 56.1 | — |

## Math

- DeepSeek V4 Pro: 64.8 (#30)
- Qwen3-30B-A3B: 37.4 (#157)

| Benchmark | DeepSeek V4 Pro | Qwen3-30B-A3B |
|---|---|---|
| MathArena Final-Answer Competitions | 76.6% | 47.8% |
| OTIS Mock AIME 2024-2025 | 98.6% | 70.3% |
| LMArena Math | 1455 | 1394 |
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| ProofBench | 50% | — |

## Knowledge

- DeepSeek V4 Pro: 59.5 (#31)
- Qwen3-30B-A3B: 41.8 (#105)

| Benchmark | DeepSeek V4 Pro | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | 91.7% | 70.1% |
| LMArena Expert | 1464 | 1396 |
| SimpleQA Verified | 52.9% | — |
| Confabulations | — | 12.3% |
| Vectara Hallucination Rate | 8.6% | — |

## Multilingual

- DeepSeek V4 Pro: 54.4 (#45)
- Qwen3-30B-A3B: 49.5 (#132)

| Benchmark | DeepSeek V4 Pro | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1439 | 1372 |
| LMArena Chinese | 1486 | 1433 |
| LMArena French | 1472 | 1418 |
| LMArena German | 1458 | 1380 |
| LMArena Japanese | 1445 | 1337 |
| LMArena Korean | 1447 | 1331 |
| LMArena Russian | 1453 | 1370 |
| LMArena Spanish | 1458 | 1404 |

## Instruction Following

- DeepSeek V4 Pro: 76.1 (#47)
- Qwen3-30B-A3B: 72.0 (#142)

| Benchmark | DeepSeek V4 Pro | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1448 | 1363 |

## Long Context

- DeepSeek V4 Pro: 45.0 (#51)
- Qwen3-30B-A3B: 31.0 (#283)

| Benchmark | DeepSeek V4 Pro | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1458 | 1379 |
| Fiction.LiveBench | — | 40.6% |
| CL-bench Life | 13.5% | — |

## Writing & Preference

- DeepSeek V4 Pro: 65.5 (#46)
- Qwen3-30B-A3B: 55.6 (#143)

| Benchmark | DeepSeek V4 Pro | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1451 | 1384 |
| LMArena Creative Writing | 1446 | 1317 |
| LMArena Multi-Turn | 1467 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
| EQ-Bench Creative Writing | 1553 | — |
| EQ-Bench 4 | 1166 | — |

## FAQ

### Is DeepSeek V4 Pro better than Qwen3-30B-A3B?

DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 38.9 on the Noometry Index. Qwen3-30B-A3B costs 4.6× 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 Qwen3-30B-A3B?

Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; DeepSeek V4 Pro lists at $0.66 and $1.98.

### Is DeepSeek V4 Pro or Qwen3-30B-A3B better for coding?

DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 37.5 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek V4 Pro does, with 1M tokens against 41K.

### How many benchmarks do DeepSeek V4 Pro and Qwen3-30B-A3B share?

28 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Qwen3-30B-A3B has 32.