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GLM-5.3 vs Llama 3.2 90B Instruct

Comparing GLM-5.3 and Llama 3.2 90B Instruct across benchmarks, pricing, and capabilities.

Zhipu AI · Meta · Updated for 2026

Which is better?

GLM-5.3 and Llama 3.2 90B Instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

On price, Llama 3.2 90B Instruct is roughly 5.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GLM-5.3 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.

Based on current benchmark, pricing, and model metadata for 2026.

Choose GLM-5.3

  • you process long inputs — it offers a 1,000,000 token context window
  • you want the most recent training data — it shipped Aug 2026

Choose Llama 3.2 90B Instruct

  • cost matters — it's about 5.9x cheaper per token
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Benchmark wins
Input price
$1.40 / M
$0.35 / M
Output price
$4.40 / M
$0.40 / M
Context window
1,000,000
128,000
Released
Aug 2026
Sep 2024
License
Unknown
Llama 3.2

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3 and Llama 3.2 90B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Pricing Analysis

Price comparison per million tokens

Llama 3.2 90B Instruct costs less

For input processing, GLM-5.3 ($1.40/1M tokens) is 4.0x more expensive than Llama 3.2 90B Instruct ($0.35/1M tokens).

For output processing, GLM-5.3 ($4.40/1M tokens) is 11.0x more expensive than Llama 3.2 90B Instruct ($0.40/1M tokens).

In conclusion, GLM-5.3 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
Mon Aug 24 2026 • llm-stats.com
Zhipu AI
GLM-5.3
Input tokens$1.40
Output tokens$4.40
Best providerUnknown Organization
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

663.0B diff

GLM-5.3 has 663.0B more parameters than Llama 3.2 90B Instruct, making it 736.7% larger.

Zhipu AI
GLM-5.3
753.0Bparameters
Meta
Llama 3.2 90B Instruct
90.0Bparameters
753.0B
GLM-5.3
90.0B
Llama 3.2 90B Instruct

Context Window

Maximum input and output token capacity

GLM-5.3 accepts 1,000,000 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-5.3
Input1,000,000 tokens
Output128,000 tokens
Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Mon Aug 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 3.2 90B Instruct supports multimodal inputs, whereas GLM-5.3 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-5.3

Text
Images
Audio
Video

Llama 3.2 90B Instruct

Text
Images
Audio
Video

Release Timeline

When each model was launched

GLM-5.3 was released on 2026-08-14, while Llama 3.2 90B Instruct was released on 2024-09-25.

GLM-5.3 is 23 months newer than Llama 3.2 90B Instruct.

GLM-5.3

Aug 14, 2026

1 weeks ago

1.9yr newer
Llama 3.2 90B Instruct

Sep 25, 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-5.3 is available from ZAI. Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic.

GLM-5.3

z logo
Unknown Organization
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M

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

Judge for yourself.

Run your own prompts against GLM-5.3 and Llama 3.2 90B Instruct side-by-side, then vote on the output you prefer.

GLM-5.3
✓ Preferred
Llama 3.2 90B Instruct
Open in Playground

FAQ

Common questions about GLM-5.3 vs Llama 3.2 90B Instruct.

Which is better, GLM-5.3 or Llama 3.2 90B Instruct?

GLM-5.3 (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-5.3 compare to Llama 3.2 90B Instruct in benchmarks?

GLM-5.3 scores Terminal-Bench 2.1: 88.2%, CyberGym: 84.5%, FrontierSWE: 78.1%, Toolathlon: 73.0%, DeepSWE 1.1: 66.9%. Llama 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%.

Is GLM-5.3 cheaper than Llama 3.2 90B Instruct?

Llama 3.2 90B Instruct is 4.0x cheaper for input tokens. GLM-5.3 costs $1.40/M input and $4.40/M output via z. 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-5.3 and Llama 3.2 90B Instruct?

GLM-5.3 supports 1.0M 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-5.3 and Llama 3.2 90B Instruct?

Key differences include context window (1.0M vs 128K), input pricing ($1.40 vs $0.35/M), multimodal support (no vs yes), licensing (Unknown vs Llama 3.2). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3 and Llama 3.2 90B Instruct?

GLM-5.3 is developed by Zhipu AI and Llama 3.2 90B Instruct is developed by Meta.