Model Comparison

Qwen3 235B-A22B (MoE) vs DeepSeek-R1

Compare the listed model data for Qwen3 235B-A22B (MoE) by Qwen and DeepSeek-R1 by DeepSeek. Benchmark and pricing records are not a controlled test and may change.

Data last updated: 2026-10-16. Verify current model details with each provider.

What the listed data says

Qwen3 235B-A22B (MoE): 128K tokens; DeepSeek-R1: 128K tokens. The listed context-window values are equal. Qwen3 235B-A22B (MoE) is listed for coding, reasoning, agentic workflows, long-context tasks; DeepSeek-R1 is listed for coding, reasoning, long-context tasks. Shared catalog benchmark entries: MMLU: Qwen3 235B-A22B (MoE) 93.5%; DeepSeek-R1 90.8%; HumanEval: Qwen3 235B-A22B (MoE) 96.2%; DeepSeek-R1 92.0%; LiveCodeBench: Qwen3 235B-A22B (MoE) 70.7%; DeepSeek-R1 65.9%; GPQA Diamond: Qwen3 235B-A22B (MoE) 71.7%; DeepSeek-R1 71.5%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.

Catalog source links

Use these model and provider links to verify current specifications, pricing, and availability.

Computed differences from catalog data

  • The listed context windows are 128K tokens and 128K tokens; the larger is 1× the smaller.
  • On shared numeric benchmark entries, MMLU: Qwen3 235B-A22B (MoE) − DeepSeek-R1 = +2.7 percentage points (93.5% vs 90.8%); HumanEval: Qwen3 235B-A22B (MoE) − DeepSeek-R1 = +4.2 percentage points (96.2% vs 92.0%); LiveCodeBench: Qwen3 235B-A22B (MoE) − DeepSeek-R1 = +4.8 percentage points (70.7% vs 65.9%); GPQA Diamond: Qwen3 235B-A22B (MoE) − DeepSeek-R1 = +0.2 percentage points (71.7% vs 71.5%).
  • The first listed parameter quantities are 235B total (22B active via MoE) and 671B total (37B active via MoE); the larger quantity is 2.86× the smaller. Total and active MoE parameters are not directly equivalent.
  • The catalog release dates are April 2025 and January 2025, about 3 months apart at the precision supplied.

Cost example: 1M input and 1M output tokens

A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.

Choose Qwen3 235B-A22B (MoE) if…

Choose Qwen3 235B-A22B (MoE) when your task aligns with catalog-listed uses or strengths such as Frontier-level coding: production systems, open-source contributions, Leetcode hard, Competition mathematics, physics, and chemistry at graduate level, Enterprise AI applications requiring highest available open-model quality, Long-form technical writing: whitepapers, research papers, documentation.

Choose DeepSeek-R1 if…

Choose DeepSeek-R1 when your task aligns with catalog-listed uses or strengths such as Competition mathematics and proof verification, Advanced software engineering: debugging complex systems, production-grade algorithms, Scientific research in physics, chemistry, biology, Enterprise AI agents needing transparent, auditable reasoning.

Qwen3 235B-A22B (MoE)

Browse Qwen models

Flagship Qwen3 — 235B total, 22B active. World-class reasoning, elite coding, 100+ languages. Rivals GPT-4o on most benchmarks.

Parameters: 235B total (22B active via MoE)

Context: 128K tokens

Catalog pricing: Open source — free to self-host. Third-party API ~$0.30-0.80/MTok

Qwen Coding · Reasoning · Agentic · Long Context Open Source

View Qwen3 235B-A22B (MoE) model profile

DeepSeek-R1

Browse DeepSeek models

Groundbreaking open reasoning model — rivals OpenAI o1 on math, science, and coding. Transparent chain-of-thought reasoning.

Parameters: 671B total (37B active via MoE)

Context: 128K tokens

Catalog pricing: Open source MIT license — free to self-host. DeepSeek API: $0.14/MTok input (cache hit), $0.55/MTok input, $2.19/MTok output

DeepSeek Coding · Reasoning · Long Context Open Source

View DeepSeek-R1 model profile

Feature Comparison — Qwen3 235B-A22B (MoE) vs DeepSeek-R1

Catalog specifications for Qwen3 235B-A22B (MoE) and DeepSeek-R1
Specification Qwen3 235B-A22B (MoE) DeepSeek-R1
Provider Qwen DeepSeek
Parameters 235B total (22B active via MoE) 671B total (37B active via MoE)
Context window 128K tokens 128K tokens
Maximum output Not listed Not listed
Catalog pricing Open source — free to self-host. Third-party API ~$0.30-0.80/MTok Open source MIT license — free to self-host. DeepSeek API: $0.14/MTok input (cache hit), $0.55/MTok input, $2.19/MTok output
Listed input/output cost per 1M tokens Separate numeric input/output rates not listed input $0.55, output $2.19 per 1M tokens
License Apache 2.0 MIT
Coding support Listed Listed
Reasoning support Listed Listed
Vision input Not listed Not listed
Multimodal Not listed Not listed
Open weights Yes Yes
Benchmark: MMLU 93.5% 90.8%
Benchmark: HumanEval 96.2% 92.0%
Benchmark: LiveCodeBench 70.7% 65.9%
Benchmark: GPQA Diamond 71.7% 71.5%

Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.

Frequently Asked Questions

What is different between Qwen3 235B-A22B (MoE) and DeepSeek-R1?
Qwen3 235B-A22B (MoE): 128K tokens; DeepSeek-R1: 128K tokens. The listed context-window values are equal. Qwen3 235B-A22B (MoE) is listed for coding, reasoning, agentic workflows, long-context tasks; DeepSeek-R1 is listed for coding, reasoning, long-context tasks. Shared catalog benchmark entries: MMLU: Qwen3 235B-A22B (MoE) 93.5%; DeepSeek-R1 90.8%; HumanEval: Qwen3 235B-A22B (MoE) 96.2%; DeepSeek-R1 92.0%; LiveCodeBench: Qwen3 235B-A22B (MoE) 70.7%; DeepSeek-R1 65.9%; GPQA Diamond: Qwen3 235B-A22B (MoE) 71.7%; DeepSeek-R1 71.5%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
What benchmark values are listed for Qwen3 235B-A22B (MoE) and DeepSeek-R1?
MMLU: Qwen3 235B-A22B (MoE) 93.5%; DeepSeek-R1 90.8%; HumanEval: Qwen3 235B-A22B (MoE) 96.2%; DeepSeek-R1 92.0%; LiveCodeBench: Qwen3 235B-A22B (MoE) 70.7%; DeepSeek-R1 65.9%; GPQA Diamond: Qwen3 235B-A22B (MoE) 71.7%; DeepSeek-R1 71.5%. The catalog values may use different versions and evaluation setups, so they are reference points rather than a controlled head-to-head result.
Which model has the larger listed context window?
Qwen3 235B-A22B (MoE): 128K tokens; DeepSeek-R1: 128K tokens. The listed context-window values are equal.
What are the listed costs per million tokens for Qwen3 235B-A22B (MoE) and DeepSeek-R1?
Qwen3 235B-A22B (MoE): Separate numeric input/output rates not listed (Open source — free to self-host. Third-party API ~$0.30-0.80/MTok). DeepSeek-R1: input $0.55, output $2.19 per 1M tokens (Open source MIT license — free to self-host. DeepSeek API: $0.14/MTok input (cache hit), $0.55/MTok input, $2.19/MTok output). Where separate numeric input and output rates are available, the worked example uses 1M input plus 1M output tokens. Confirm current terms with each provider.
How far apart are the listed release dates for Qwen3 235B-A22B (MoE) and DeepSeek-R1?
The catalog lists Qwen3 235B-A22B (MoE) as April 2025 and DeepSeek-R1 as January 2025, about 3 months apart at the precision supplied.
When was the comparison data last updated?
The model catalog records 2026-10-16 as its data update date. Provider specifications and prices may have changed since then.
How should I choose between Qwen3 235B-A22B (MoE) and DeepSeek-R1?
Compare the listed specifications and capabilities, review the benchmark notes, then test both with the same representative prompt for your task. This page does not claim a universal winner.

Explore these models and related comparisons

Read the Qwen3 235B-A22B (MoE) model profile and DeepSeek-R1 model profile, or browse the model directory.

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