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GLM-5.3-Flash vs Grok-4.1 Thinking

Comparing GLM-5.3-Flash and Grok-4.1 Thinking across benchmarks, pricing, and capabilities.

Zhipu AI · xAI · Updated for 2026

Which is better?

GLM-5.3-Flash and Grok-4.1 Thinking trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

On price, GLM-5.3-Flash is roughly 25.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GLM-5.3-Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

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

Choose GLM-5.3-Flash

  • cost matters — it's about 25.3x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Aug 2026
  • you need open weights you can self-host or fine-tune

Choose Grok-4.1 Thinking

  • you want predictable pricing at $3.00/M input and $15.00/M output

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.15 / M
$3.00 / M
Output price
$0.50 / M
$15.00 / M
Context window
1,048,576
256,000
Released
Aug 2026
Nov 2025
License
MIT
Proprietary

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3-Flash and Grok-4.1 Thinkingdon'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

GLM-5.3-Flash costs less

For input processing, GLM-5.3-Flash ($0.15/1M tokens) is 20.0x cheaper than Grok-4.1 Thinking ($3.00/1M tokens).

For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 30.0x cheaper than Grok-4.1 Thinking ($15.00/1M tokens).

In conclusion, Grok-4.1 Thinking is more expensive than GLM-5.3-Flash.*

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

Lowest available price from all providers
Wed Aug 26 2026 • llm-stats.com
Zhipu AI
GLM-5.3-Flash
Input tokens$0.15
Output tokens$0.50
Best providerDeepinfra
xAI
Grok-4.1 Thinking
Input tokens$3.00
Output tokens$15.00
Best providerxAI
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

GLM-5.3-Flash accepts 1,048,576 input tokens compared to Grok-4.1 Thinking's 256,000 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while Grok-4.1 Thinking is limited to 8,000 tokens.

Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
xAI
Grok-4.1 Thinking
Input256,000 tokens
Output8,000 tokens
Wed Aug 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both GLM-5.3-Flash and Grok-4.1 Thinking support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GLM-5.3-Flash

Text
Images
Audio
Video

Grok-4.1 Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash is licensed under MIT, while Grok-4.1 Thinking uses a proprietary license.

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

GLM-5.3-Flash

MIT

Open weights

Grok-4.1 Thinking

Proprietary

Closed source

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while Grok-4.1 Thinking was released on 2025-11-17.

GLM-5.3-Flash is 9 months newer than Grok-4.1 Thinking.

GLM-5.3-Flash

Aug 26, 2026

0 days ago

9mo newer
Grok-4.1 Thinking

Nov 17, 2025

9 months 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-5.3-Flash is available from DeepInfra, Novita, ZAI. Grok-4.1 Thinking is available from xAI.

GLM-5.3-Flash

deepinfra logo
Deepinfra
Input Price:Input: $0.15/1MOutput Price:Output: $0.50/1M
novita logo
Novita
Input Price:Input: $0.15/1MOutput Price:Output: $0.50/1M
z logo
Unknown Organization
Input Price:Input: $0.15/1MOutput Price:Output: $0.50/1M

Grok-4.1 Thinking

xai logo
xAI
Input Price:Input: $3.00/1MOutput Price:Output: $15.00/1M
* 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 GLM-5.3-Flash and Grok-4.1 Thinking side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
Grok-4.1 Thinking
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs Grok-4.1 Thinking.

Which is better, GLM-5.3-Flash or Grok-4.1 Thinking?

GLM-5.3-Flash (Zhipu AI) and Grok-4.1 Thinking (xAI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does GLM-5.3-Flash compare to Grok-4.1 Thinking in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%. Grok-4.1 Thinking scores Creative Writing v3: 86.1%, WMDP: 84.0%, EQ-Bench: 79.3%, ProtocolQA: 79.0%, LMArena Text Leaderboard: 74.2%.

Is GLM-5.3-Flash cheaper than Grok-4.1 Thinking?

GLM-5.3-Flash is 20.0x cheaper for input tokens. GLM-5.3-Flash costs $0.15/M input and $0.50/M output via deepinfra. Grok-4.1 Thinking costs $3.00/M input and $15.00/M output via xai.

What are the context window sizes for GLM-5.3-Flash and Grok-4.1 Thinking?

GLM-5.3-Flash supports 1.0M tokens and Grok-4.1 Thinking 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 GLM-5.3-Flash and Grok-4.1 Thinking?

Key differences include context window (1.0M vs 256K), input pricing ($0.15 vs $3.00/M), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3-Flash and Grok-4.1 Thinking?

GLM-5.3-Flash is developed by Zhipu AI and Grok-4.1 Thinking is developed by xAI.