Model Comparison

GLM-5 vs Devstral Small 1.1Which is better in 2026?

GLM-5 significantly outperforms across most benchmarks. Devstral Small 1.1 is 10.3x cheaper per token.

Verdict: GLM-5 vs Devstral Small 1.1 — which is better?

GLM-5 (by Zhipu AI) and Devstral Small 1.1 (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.

GLM-5 outperforms in 1 benchmarks (SWE-Bench Verified), while Devstral Small 1.1 is better at 0 benchmarks. GLM-5 significantly outperforms across most benchmarks.

On price, Devstral Small 1.1 is roughly 10.3x 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 want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you process long inputs — it offers a 200,000 token context window
  • you want the most recent training data — it shipped Feb 2026

Choose Devstral Small 1.1 if…

  • cost matters — it's about 10.3x cheaper per token
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GLM-5 outperforms in 1 benchmarks (SWE-Bench Verified), while Devstral Small 1.1 is better at 0 benchmarks.

GLM-5 significantly outperforms across most benchmarks.

Sat Jun 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Devstral Small 1.1 costs less

For input processing, GLM-5 ($1.00/1M tokens) is 10.0x more expensive than Devstral Small 1.1 ($0.10/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 10.7x more expensive than Devstral Small 1.1 ($0.30/1M tokens).

In conclusion, GLM-5 is more expensive than Devstral Small 1.1.*

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

Lowest available price from all providers
Sat Jun 13 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerFriendliAI
Mistral AI
Devstral Small 1.1
Input tokens$0.10
Output tokens$0.30
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

720.0B diff

GLM-5 has 720.0B more parameters than Devstral Small 1.1, making it 3000.0% larger.

Zhipu AI
GLM-5
744.0Bparameters
Mistral AI
Devstral Small 1.1
24.0Bparameters
744.0B
GLM-5
24.0B
Devstral Small 1.1

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to Devstral Small 1.1's 128,000 tokens. Both models can generate responses up to 128,000 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Mistral AI
Devstral Small 1.1
Input128,000 tokens
Output128,000 tokens
Sat Jun 13 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Devstral Small 1.1 uses Apache 2.0.

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

GLM-5

MIT

Open weights

Devstral Small 1.1

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Devstral Small 1.1 was released on 2025-07-11.

GLM-5 is 7 months newer than Devstral Small 1.1.

GLM-5

Feb 11, 2026

4 months ago

7mo newer
Devstral Small 1.1

Jul 11, 2025

11 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 is available from FriendliAI, ZAI. Devstral Small 1.1 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

Devstral Small 1.1

mistral logo
Mistral
Input Price:Input: $0.10/1MOutput Price:Output: $0.30/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI
Larger context window (200,000 tokens)
Higher SWE-Bench Verified score (77.8% vs 53.6%)
Mistral AI
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Mistral AI
Devstral Small 1.1

FAQ

Common questions about GLM-5 vs Devstral Small 1.1.

Which is better, GLM-5 or Devstral Small 1.1?

GLM-5 significantly outperforms across most benchmarks. GLM-5 is made by Zhipu AI and Devstral Small 1.1 is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GLM-5 compare to Devstral Small 1.1 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%. Devstral Small 1.1 scores SWE-Bench Verified: 53.6%.

Is GLM-5 cheaper than Devstral Small 1.1?

Devstral Small 1.1 is 10.0x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. Devstral Small 1.1 costs $0.10/M input and $0.30/M output via mistral.

What are the context window sizes for GLM-5 and Devstral Small 1.1?

GLM-5 supports 200K tokens and Devstral Small 1.1 supports 128K 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 Devstral Small 1.1?

Key differences include context window (200K vs 128K), input pricing ($1.00 vs $0.10/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Devstral Small 1.1?

GLM-5 is developed by Zhipu AI and Devstral Small 1.1 is developed by Mistral AI.

Related comparisons