Model Comparison

GLM-4.7-Flash vs Qwen3-235B-A22B-Instruct-2507Which is better in 2026?

Both models are evenly matched across the benchmarks. GLM-4.7-Flash is 2.0x cheaper per token.

Verdict: GLM-4.7-Flash vs Qwen3-235B-A22B-Instruct-2507 — which is better?

GLM-4.7-Flash (by Zhipu AI) and Qwen3-235B-A22B-Instruct-2507 (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

GLM-4.7-Flash outperforms in 1 benchmarks (AIME 2025), while Qwen3-235B-A22B-Instruct-2507 is better at 1 benchmark (GPQA). Both models are evenly matched across the benchmarks.

On price, GLM-4.7-Flash is roughly 2.0x 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.

Choose GLM-4.7-Flash if…

  • cost matters — it's about 2.0x cheaper per token
  • you want the most recent training data — it shipped Jan 2026

Choose Qwen3-235B-A22B-Instruct-2507 if…

  • you process long inputs — it offers a 262,144 token context window

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

GLM-4.7-Flash outperforms in 1 benchmarks (AIME 2025), while Qwen3-235B-A22B-Instruct-2507 is better at 1 benchmark (GPQA).

Both models are evenly matched across the benchmarks.

Sun Jul 26 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GLM-4.7-Flash costs less

For input processing, GLM-4.7-Flash ($0.07/1M tokens) is 2.1x cheaper than Qwen3-235B-A22B-Instruct-2507 ($0.15/1M tokens).

For output processing, GLM-4.7-Flash ($0.40/1M tokens) is 2.0x cheaper than Qwen3-235B-A22B-Instruct-2507 ($0.80/1M tokens).

In conclusion, Qwen3-235B-A22B-Instruct-2507 is more expensive than GLM-4.7-Flash.*

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

Lowest available price from all providers
Sun Jul 26 2026 • llm-stats.com
Zhipu AI
GLM-4.7-Flash
Input tokens$0.07
Output tokens$0.40
Best providerUnknown Organization
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

205.0B diff

Qwen3-235B-A22B-Instruct-2507 has 205.0B more parameters than GLM-4.7-Flash, making it 683.3% larger.

Zhipu AI
GLM-4.7-Flash
30.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
235.0Bparameters
30.0B
GLM-4.7-Flash
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 GLM-4.7-Flash's 128,000 tokens. Qwen3-235B-A22B-Instruct-2507 can generate longer responses up to 131,072 tokens, while GLM-4.7-Flash is limited to 16,384 tokens.

Zhipu AI
GLM-4.7-Flash
Input128,000 tokens
Output16,384 tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input262,144 tokens
Output131,072 tokens
Sun Jul 26 2026 • llm-stats.com

License

Usage and distribution terms

GLM-4.7-Flash 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.

GLM-4.7-Flash

MIT

Open weights

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-4.7-Flash was released on 2026-01-19, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.

GLM-4.7-Flash is 6 months newer than Qwen3-235B-A22B-Instruct-2507.

GLM-4.7-Flash

Jan 19, 2026

6 months ago

6mo newer
Qwen3-235B-A22B-Instruct-2507

Jul 22, 2025

1.0 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

GLM-4.7-Flash is available from ZAI. Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita.

GLM-4.7-Flash

z logo
Unknown Organization
Input Price:Input: $0.07/1MOutput Price:Output: $0.40/1M

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

Zhipu AI
Less expensive input tokens
Less expensive output tokens
Higher AIME 2025 score (91.6% vs 70.3%)
Alibaba Cloud / Qwen Team
Larger context window (262,144 tokens)
Higher GPQA score (77.5% vs 75.2%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against GLM-4.7-Flash and Qwen3-235B-A22B-Instruct-2507 side-by-side, then vote on the output you prefer.

GLM-4.7-Flash
✓ Preferred
Qwen3-235B-A22B-Instruct-2507
Open in Playground
AI Model Comparison Table
Feature
Zhipu AI
GLM-4.7-Flash
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507

FAQ

Common questions about GLM-4.7-Flash vs Qwen3-235B-A22B-Instruct-2507.

Which is better, GLM-4.7-Flash or Qwen3-235B-A22B-Instruct-2507?

Both models are evenly matched across the benchmarks. GLM-4.7-Flash is made by Zhipu AI 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.

How does GLM-4.7-Flash compare to Qwen3-235B-A22B-Instruct-2507 in benchmarks?

GLM-4.7-Flash scores AIME 2025: 91.6%, Tau-bench: 79.5%, GPQA: 75.2%, SWE-Bench Verified: 59.2%, BrowseComp: 42.8%. 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 GLM-4.7-Flash cheaper than Qwen3-235B-A22B-Instruct-2507?

GLM-4.7-Flash is 2.1x cheaper for input tokens. GLM-4.7-Flash costs $0.07/M input and $0.40/M output via z. Qwen3-235B-A22B-Instruct-2507 costs $0.15/M input and $0.80/M output via fireworks.

What are the context window sizes for GLM-4.7-Flash and Qwen3-235B-A22B-Instruct-2507?

GLM-4.7-Flash supports 128K 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.

What are the main differences between GLM-4.7-Flash and Qwen3-235B-A22B-Instruct-2507?

Key differences include context window (128K vs 262K), input pricing ($0.07 vs $0.15/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.7-Flash and Qwen3-235B-A22B-Instruct-2507?

GLM-4.7-Flash is developed by Zhipu AI and Qwen3-235B-A22B-Instruct-2507 is developed by Alibaba Cloud / Qwen Team.

Related comparisons