Model Comparison

GLM-5 vs Mistral NeMo InstructWhich is better in 2026?

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

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

GLM-5 (by Zhipu AI) and Mistral NeMo Instruct (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 NeMo Instruct 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 process long inputs — it offers a 200,000 token context window
  • you want the most recent training data — it shipped Feb 2026

Choose Mistral NeMo Instruct if…

  • cost matters — it's about 10.3x cheaper per token
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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Mistral NeMo Instruct 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 NeMo Instruct costs less

For input processing, GLM-5 ($1.00/1M tokens) is 6.7x more expensive than Mistral NeMo Instruct ($0.15/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 21.3x more expensive than Mistral NeMo Instruct ($0.15/1M tokens).

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

* 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
Mistral AI
Mistral NeMo Instruct
Input tokens$0.15
Output tokens$0.15
Best providerGoogle
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

732.0B diff

GLM-5 has 732.0B more parameters than Mistral NeMo Instruct, making it 6100.0% larger.

Zhipu AI
GLM-5
744.0Bparameters
Mistral AI
Mistral NeMo Instruct
12.0Bparameters
744.0B
GLM-5
12.0B
Mistral NeMo Instruct

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to Mistral NeMo Instruct'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
Mistral NeMo Instruct
Input128,000 tokens
Output128,000 tokens
Sat Jun 06 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Mistral NeMo Instruct 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

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Mistral NeMo Instruct was released on 2024-07-18.

GLM-5 is 19 months newer than Mistral NeMo Instruct.

GLM-5

Feb 11, 2026

3 months ago

1.6yr newer
Mistral NeMo Instruct

Jul 18, 2024

1.9 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 NeMo Instruct is available from Google, 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 NeMo Instruct

google logo
Google
Input Price:Input: $0.15/1MOutput Price:Output: $0.15/1M
mistral logo
Mistral
Input Price:Input: $0.15/1MOutput Price:Output: $0.15/1M
* Prices shown are per million tokens

Outputs Comparison

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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 NeMo Instruct

FAQ

Common questions about GLM-5 vs Mistral NeMo Instruct.

Which is better, GLM-5 or Mistral NeMo Instruct?

GLM-5 (Zhipu AI) and Mistral NeMo Instruct (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 NeMo Instruct 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%. Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%.

Is GLM-5 cheaper than Mistral NeMo Instruct?

Mistral NeMo Instruct is 6.7x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. Mistral NeMo Instruct costs $0.15/M input and $0.15/M output via google.

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

GLM-5 supports 200K tokens and Mistral NeMo Instruct 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 Mistral NeMo Instruct?

Key differences include context window (200K vs 128K), input pricing ($1.00 vs $0.15/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Mistral NeMo Instruct?

GLM-5 is developed by Zhipu AI and Mistral NeMo Instruct is developed by Mistral AI.

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