Model Comparison

GLM-5 vs Llama 3.2 90B InstructWhich is better in 2026?

Comparing GLM-5 and Llama 3.2 90B Instruct across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Llama 3.2 90B Instruct — which is better?

GLM-5 (by Zhipu AI) and Llama 3.2 90B Instruct (by Meta) 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, Llama 3.2 90B Instruct is roughly 4.3x 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 Llama 3.2 90B Instruct if…

  • cost matters — it's about 4.3x cheaper per token
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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Llama 3.2 90B 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

Llama 3.2 90B Instruct costs less

For input processing, GLM-5 ($1.00/1M tokens) is 2.9x more expensive than Llama 3.2 90B Instruct ($0.35/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 8.0x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).

In conclusion, GLM-5 is more expensive than Llama 3.2 90B 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
Meta
Llama 3.2 90B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

654.0B diff

GLM-5 has 654.0B more parameters than Llama 3.2 90B Instruct, making it 726.7% larger.

Zhipu AI
GLM-5
744.0Bparameters
Meta
Llama 3.2 90B Instruct
90.0Bparameters
744.0B
GLM-5
90.0B
Llama 3.2 90B Instruct

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to Llama 3.2 90B 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
Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Sat Jun 06 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 3.2 90B Instruct supports multimodal inputs, whereas GLM-5 does not.

Llama 3.2 90B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text
Images
Audio
Video

Llama 3.2 90B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Llama 3.2 90B Instruct uses Llama 3.2.

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

GLM-5

MIT

Open weights

Llama 3.2 90B Instruct

Llama 3.2

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Llama 3.2 90B Instruct was released on 2024-09-25.

GLM-5 is 17 months newer than Llama 3.2 90B Instruct.

GLM-5

Feb 11, 2026

3 months ago

1.4yr newer
Llama 3.2 90B Instruct

Sep 25, 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. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.

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

Llama 3.2 90B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.72/1MOutput Price:Output: $0.72/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
together logo
Together
Input Price:Input: $1.20/1MOutput Price:Output: $1.20/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M
* 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)
Meta
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Meta
Llama 3.2 90B Instruct

FAQ

Common questions about GLM-5 vs Llama 3.2 90B Instruct.

Which is better, GLM-5 or Llama 3.2 90B Instruct?

GLM-5 (Zhipu AI) and Llama 3.2 90B Instruct (Meta) 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 Llama 3.2 90B 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%. Llama 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%.

Is GLM-5 cheaper than Llama 3.2 90B Instruct?

Llama 3.2 90B Instruct is 2.9x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. Llama 3.2 90B Instruct costs $0.35/M input and $0.40/M output via deepinfra.

What are the context window sizes for GLM-5 and Llama 3.2 90B Instruct?

GLM-5 supports 200K tokens and Llama 3.2 90B 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 Llama 3.2 90B Instruct?

Key differences include context window (200K vs 128K), input pricing ($1.00 vs $0.35/M), multimodal support (no vs yes), licensing (MIT vs Llama 3.2). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Llama 3.2 90B Instruct?

GLM-5 is developed by Zhipu AI and Llama 3.2 90B Instruct is developed by Meta.

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