Model Comparison

DeepSeek-V3 vs Qwen3-235B-A22B-Instruct-2507

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks. Qwen3-235B-A22B-Instruct-2507 is 1.5x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

DeepSeek-V3 outperforms in 0 benchmarks, while Qwen3-235B-A22B-Instruct-2507 is better at 7 benchmarks (Aider-Polyglot, CSimpleQA, GPQA, IFEval, MMLU-Pro, MMLU-Redux, SimpleQA).

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks.

Wed Apr 29 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3-235B-A22B-Instruct-2507 costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 1.8x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.15/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 1.4x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.80/1M tokens).

In conclusion, DeepSeek-V3 is more expensive than Qwen3-235B-A22B-Instruct-2507.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Wed Apr 29 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input tokens$0.15
Output tokens$0.80
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

436.0B diff

DeepSeek-V3 has 436.0B more parameters than Qwen3-235B-A22B-Instruct-2507, making it 185.5% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
235.0Bparameters
671.0B
DeepSeek-V3
235.0B
Qwen3-235B-A22B-Instruct-2507

Context Window

Maximum input and output token capacity

Qwen3-235B-A22B-Instruct-2507 accepts 262,144 input tokens compared to DeepSeek-V3's 131,072 tokens. Both models can generate responses up to 131,072 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input262,144 tokens
Output131,072 tokens
Wed Apr 29 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Qwen3-235B-A22B-Instruct-2507 uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.

Qwen3-235B-A22B-Instruct-2507 is 7 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

Qwen3-235B-A22B-Instruct-2507

Jul 22, 2025

9 months ago

6mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-V3 is available from DeepSeek. Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

Qwen3-235B-A22B-Instruct-2507

fireworks logo
Fireworks
Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M
novita logo
Novita
Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Alibaba Cloud / Qwen Team
Larger context window (262,144 tokens)
Less expensive input tokens
Less expensive output tokens
Higher Aider-Polyglot score (57.3% vs 49.6%)
Higher CSimpleQA score (84.3% vs 64.8%)
Higher GPQA score (77.5% vs 59.1%)
Higher IFEval score (88.7% vs 86.1%)
Higher MMLU-Pro score (83.0% vs 75.9%)
Higher MMLU-Redux score (93.1% vs 89.1%)
Higher SimpleQA score (54.3% vs 24.9%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507

FAQ

Common questions about DeepSeek-V3 vs Qwen3-235B-A22B-Instruct-2507

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and Qwen3-235B-A22B-Instruct-2507 is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Qwen3-235B-A22B-Instruct-2507 scores ZebraLogic: 95.0%, MMLU-Redux: 93.1%, IFEval: 88.7%, MultiPL-E: 87.9%, Creative Writing v3: 87.5%.
Qwen3-235B-A22B-Instruct-2507 is 1.8x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Qwen3-235B-A22B-Instruct-2507 costs $0.15/M input and $0.80/M output via fireworks.
DeepSeek-V3 supports 131K tokens and Qwen3-235B-A22B-Instruct-2507 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 262K), input pricing ($0.27 vs $0.15/M), licensing (MIT + Model License (Commercial use allowed) vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and Qwen3-235B-A22B-Instruct-2507 is developed by Alibaba Cloud / Qwen Team.