Model Comparison

GLM-5 vs Gemini 2.0 Flash-LiteWhich is better in 2026?

Comparing GLM-5 and Gemini 2.0 Flash-Lite across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Gemini 2.0 Flash-Lite — which is better?

GLM-5 (by Zhipu AI) and Gemini 2.0 Flash-Lite (by Google) 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.

On price, Gemini 2.0 Flash-Lite is roughly 12.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 2.0 Flash-Lite also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Choose GLM-5 if…

  • you want the most recent training data — it shipped Feb 2026
  • you need open weights you can self-host or fine-tune

Choose Gemini 2.0 Flash-Lite if…

  • cost matters — it's about 12.2x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Gemini 2.0 Flash-Lite 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

Gemini 2.0 Flash-Lite costs less

For input processing, GLM-5 ($1.00/1M tokens) is 14.3x more expensive than Gemini 2.0 Flash-Lite ($0.07/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 10.7x more expensive than Gemini 2.0 Flash-Lite ($0.30/1M tokens).

In conclusion, GLM-5 is more expensive than Gemini 2.0 Flash-Lite.*

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

Lowest available price from all providers
Sat Jun 06 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerFriendliAI
Google
Gemini 2.0 Flash-Lite
Input tokens$0.07
Output tokens$0.30
Best providerGoogle
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

Gemini 2.0 Flash-Lite accepts 1,048,576 input tokens compared to GLM-5's 200,000 tokens. GLM-5 can generate longer responses up to 128,000 tokens, while Gemini 2.0 Flash-Lite is limited to 8,192 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Google
Gemini 2.0 Flash-Lite
Input1,048,576 tokens
Output8,192 tokens
Sat Jun 06 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.0 Flash-Lite supports multimodal inputs, whereas GLM-5 does not.

Gemini 2.0 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text
Images
Audio
Video

Gemini 2.0 Flash-Lite

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Gemini 2.0 Flash-Lite uses a proprietary license.

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

GLM-5

MIT

Open weights

Gemini 2.0 Flash-Lite

Proprietary

Closed source

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Gemini 2.0 Flash-Lite was released on 2025-02-05.

GLM-5 is 12 months newer than Gemini 2.0 Flash-Lite.

GLM-5

Feb 11, 2026

3 months ago

1.0yr newer
Gemini 2.0 Flash-Lite

Feb 5, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash-Lite has a documented knowledge cutoff of 2024-06-01, while GLM-5's cutoff date is not specified.

We can confirm Gemini 2.0 Flash-Lite's training data extends to 2024-06-01, but cannot make a direct comparison without GLM-5's cutoff date.

GLM-5

Gemini 2.0 Flash-Lite

Jun 2024

Provider Availability

GLM-5 is available from FriendliAI, ZAI. Gemini 2.0 Flash-Lite is available from Google.

GLM-5

friendli logo
FriendliAI
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M
z logo
Unknown Organization
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

Gemini 2.0 Flash-Lite

google logo
Google
Input Price:Input: $0.07/1MOutput Price:Output: $0.30/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Has open weights
Larger context window (1,048,576 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Google
Gemini 2.0 Flash-Lite

FAQ

Common questions about GLM-5 vs Gemini 2.0 Flash-Lite.

Which is better, GLM-5 or Gemini 2.0 Flash-Lite?

GLM-5 (Zhipu AI) and Gemini 2.0 Flash-Lite (Google) 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 compare to Gemini 2.0 Flash-Lite in benchmarks?

GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. Gemini 2.0 Flash-Lite scores MATH: 86.8%, FACTS Grounding: 83.6%, Global-MMLU-Lite: 78.2%, MMLU-Pro: 71.6%, MMMU: 68.0%.

Is GLM-5 cheaper than Gemini 2.0 Flash-Lite?

Gemini 2.0 Flash-Lite is 14.3x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. Gemini 2.0 Flash-Lite costs $0.07/M input and $0.30/M output via google.

What are the context window sizes for GLM-5 and Gemini 2.0 Flash-Lite?

GLM-5 supports 200K tokens and Gemini 2.0 Flash-Lite supports 1.0M 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 and Gemini 2.0 Flash-Lite?

Key differences include context window (200K vs 1.0M), input pricing ($1.00 vs $0.07/M), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Gemini 2.0 Flash-Lite?

GLM-5 is developed by Zhipu AI and Gemini 2.0 Flash-Lite is developed by Google.