Model Comparison

GLM-5 vs Mistral SmallWhich is better in 2026?

Comparing GLM-5 and Mistral Small across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Mistral Small — which is better?

GLM-5 (by Zhipu AI) and Mistral Small (by Mistral AI) 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, Mistral Small is roughly 5.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GLM-5 also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose GLM-5 if…

  • you process long inputs — it offers a 200,000 token context window
  • you want the most recent training data — it shipped Feb 2026

Choose Mistral Small if…

  • cost matters — it's about 5.2x cheaper per token
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Mistral Small 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

Mistral Small costs less

For input processing, GLM-5 ($1.00/1M tokens) is 5.0x more expensive than Mistral Small ($0.20/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 5.3x more expensive than Mistral Small ($0.60/1M tokens).

In conclusion, GLM-5 is more expensive than Mistral Small.*

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

Lowest available price from all providers
Sun Jun 07 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerFriendliAI
Mistral AI
Mistral Small
Input tokens$0.20
Output tokens$0.60
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

722.0B diff

GLM-5 has 722.0B more parameters than Mistral Small, making it 3281.8% larger.

Zhipu AI
GLM-5
744.0Bparameters
Mistral AI
Mistral Small
22.0Bparameters
744.0B
GLM-5
22.0B
Mistral Small

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to Mistral Small's 32,768 tokens. GLM-5 can generate longer responses up to 128,000 tokens, while Mistral Small is limited to 32,768 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Mistral AI
Mistral Small
Input32,768 tokens
Output32,768 tokens
Sun Jun 07 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Mistral Small uses Mistral Research License.

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

GLM-5

MIT

Open weights

Mistral Small

Mistral Research License

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Mistral Small was released on 2024-09-17.

GLM-5 is 17 months newer than Mistral Small.

GLM-5

Feb 11, 2026

3 months ago

1.4yr newer
Mistral Small

Sep 17, 2024

1.7 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-5 is available from FriendliAI, ZAI. Mistral Small is available from Mistral AI.

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

Mistral Small

mistral logo
Mistral
Input Price:Input: $0.20/1MOutput Price:Output: $0.60/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI
Larger context window (200,000 tokens)
Mistral AI
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Mistral AI
Mistral Small

FAQ

Common questions about GLM-5 vs Mistral Small.

Which is better, GLM-5 or Mistral Small?

GLM-5 (Zhipu AI) and Mistral Small (Mistral AI) 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 Mistral Small 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%.

Is GLM-5 cheaper than Mistral Small?

Mistral Small is 5.0x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. Mistral Small costs $0.20/M input and $0.60/M output via mistral.

What are the context window sizes for GLM-5 and Mistral Small?

GLM-5 supports 200K tokens and Mistral Small supports 33K 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 Mistral Small?

Key differences include context window (200K vs 33K), input pricing ($1.00 vs $0.20/M), licensing (MIT vs Mistral Research License). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Mistral Small?

GLM-5 is developed by Zhipu AI and Mistral Small is developed by Mistral AI.

Related comparisons