Model Comparison

DeepSeek-R1 vs Qwen3-235B-A22B-Instruct-2507

Comparing DeepSeek-R1 and Qwen3-235B-A22B-Instruct-2507 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and Qwen3-235B-A22B-Instruct-2507 don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

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

For input processing, DeepSeek-R1 ($0.55/1M tokens) is 3.7x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.15/1M tokens).

For output processing, DeepSeek-R1 ($2.19/1M tokens) is 2.7x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.80/1M tokens).

In conclusion, DeepSeek-R1 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

Mon Apr 20 2026 • llm-stats.com

DeepSeek-R1

Input tokens$0.55

Output tokens$2.19

Best providerDeepSeek

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-R1 has 436.0B more parameters than Qwen3-235B-A22B-Instruct-2507, making it 185.5% larger.

DeepSeek-R1

671.0Bparameters

Qwen3-235B-A22B-Instruct-2507

235.0Bparameters

671.0B

DeepSeek-R1

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-R1's 131,072 tokens. Both models can generate responses up to 131,072 tokens.

DeepSeek-R1

Input131,072 tokens

Output131,072 tokens

Qwen3-235B-A22B-Instruct-2507

Input262,144 tokens

Output131,072 tokens

Mon Apr 20 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, 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-R1

MIT

Open weights

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.

Qwen3-235B-A22B-Instruct-2507 is 6 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.2 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-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita.

DeepSeek-R1

DeepSeek

Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M

Deepinfra

Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M

Together

Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M

Fireworks

Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

Qwen3-235B-A22B-Instruct-2507

Fireworks

Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M

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

Qwen3-235B-A22B-Instruct-2507

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Less expensive input tokens

Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature	DeepSeek-R1	Qwen3-235B-A22B-Instruct-2507

FAQ

Common questions about DeepSeek-R1 vs Qwen3-235B-A22B-Instruct-2507

DeepSeek-R1 (DeepSeek) and Qwen3-235B-A22B-Instruct-2507 (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

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 3.7x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/M output via deepseek. Qwen3-235B-A22B-Instruct-2507 costs $0.15/M input and $0.80/M output via fireworks.

DeepSeek-R1 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 ($0.55 vs $0.15/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

DeepSeek-R1 is developed by DeepSeek and Qwen3-235B-A22B-Instruct-2507 is developed by Alibaba Cloud / Qwen Team.

DeepSeek-R1 vs Qwen3-235B-A22B-Instruct-2507

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

License

Release Timeline

Knowledge Cutoff

Provider Availability

DeepSeek-R1

Qwen3-235B-A22B-Instruct-2507

Outputs Comparison

Key Takeaways

DeepSeek-R1

Qwen3-235B-A22B-Instruct-2507

Detailed Comparison

FAQ

Which is better, DeepSeek-R1 or Qwen3-235B-A22B-Instruct-2507?

How does DeepSeek-R1 compare to Qwen3-235B-A22B-Instruct-2507 in benchmarks?

Is DeepSeek-R1 cheaper than Qwen3-235B-A22B-Instruct-2507?

What are the context window sizes for DeepSeek-R1 and Qwen3-235B-A22B-Instruct-2507?

What are the main differences between DeepSeek-R1 and Qwen3-235B-A22B-Instruct-2507?

Who makes DeepSeek-R1 and Qwen3-235B-A22B-Instruct-2507?