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Qwen3-235B-A22B-Instruct-2507 vs Qwen3-Coder

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

Alibaba Cloud / Qwen Team · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3-235B-A22B-Instruct-2507 and Qwen3-Coder trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

On price, Qwen3-Coder is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3-235B-A22B-Instruct-2507 also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Based on current benchmark, pricing, and model metadata for 2026.

Choose Qwen3-235B-A22B-Instruct-2507

  • you process long inputs — it offers a 262,144 token context window
  • you want the most recent training data — it shipped Jul 2025

Choose Qwen3-Coder

  • cost matters — it's about 1.7x cheaper per token

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.15 / M
$0.18 / M
Output price
$0.80 / M
$0.18 / M
Context window
262,144
256,000
Released
Jul 2025
Jan 2025
License
Apache 2.0
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

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

Arena Performance

Playground indexes and blind preference scores

Pricing Analysis

Price comparison per million tokens

Qwen3-Coder costs less

For input processing, Qwen3-235B-A22B-Instruct-2507 ($0.15/1M tokens) is 1.2x cheaper than Qwen3-Coder ($0.18/1M tokens).

For output processing, Qwen3-235B-A22B-Instruct-2507 ($0.80/1M tokens) is 4.4x more expensive than Qwen3-Coder ($0.18/1M tokens).

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

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

Lowest available price from all providers
Wed Aug 26 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input tokens$0.15
Output tokens$0.80
Best providerFireworks
Alibaba Cloud / Qwen Team
Qwen3-Coder
Input tokens$0.18
Output tokens$0.18
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

245.0B diff

Qwen3-Coder has 245.0B more parameters than Qwen3-235B-A22B-Instruct-2507, making it 104.3% larger.

Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
235.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-Coder
480.0Bparameters
235.0B
Qwen3-235B-A22B-Instruct-2507
480.0B
Qwen3-Coder

Context Window

Maximum input and output token capacity

Qwen3-235B-A22B-Instruct-2507 accepts 262,144 input tokens compared to Qwen3-Coder's 256,000 tokens. Qwen3-Coder can generate longer responses up to 256,000 tokens, while Qwen3-235B-A22B-Instruct-2507 is limited to 131,072 tokens.

Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input262,144 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3-Coder
Input256,000 tokens
Output256,000 tokens
Wed Aug 26 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Qwen3-Coder

Apache 2.0

Open weights

Release Timeline

When each model was launched

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

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

Qwen3-235B-A22B-Instruct-2507

Jul 22, 2025

1.1 years ago

6mo newer
Qwen3-Coder

Jan 1, 2025

1.6 years ago

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

Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita. Qwen3-Coder is available from DeepInfra, Fireworks.

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

Qwen3-Coder

deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M
fireworks logo
Fireworks
Input Price:Input: $0.25/1MOutput Price:Output: $0.25/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Qwen3-235B-A22B-Instruct-2507 and Qwen3-Coder side-by-side, then vote on the output you prefer.

Qwen3-235B-A22B-Instruct-2507
✓ Preferred
Qwen3-Coder
Open in Playground

FAQ

Common questions about Qwen3-235B-A22B-Instruct-2507 vs Qwen3-Coder.

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

Qwen3-235B-A22B-Instruct-2507 (Alibaba Cloud / Qwen Team) and Qwen3-Coder (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.

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

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%.

Is Qwen3-235B-A22B-Instruct-2507 cheaper than Qwen3-Coder?

Qwen3-235B-A22B-Instruct-2507 is 1.2x cheaper for input tokens. Qwen3-235B-A22B-Instruct-2507 costs $0.15/M input and $0.80/M output via fireworks. Qwen3-Coder costs $0.18/M input and $0.18/M output via deepinfra.

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

Qwen3-235B-A22B-Instruct-2507 supports 262K tokens and Qwen3-Coder supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

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

Key differences include context window (262K vs 256K), input pricing ($0.15 vs $0.18/M). See the full comparison above for benchmark-by-benchmark results.