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GLM-4.6 vs Llama 3.2 3B Instruct
Comprehensive side-by-side LLM comparison
GLM-4.6 leads with 48.2% higher average benchmark score. Llama 3.2 3B Instruct offers 59.4K more tokens in context window than GLM-4.6. Llama 3.2 3B Instruct is $2.57 cheaper per million tokens. GLM-4.6 supports multimodal inputs. Overall, GLM-4.6 is the stronger choice for coding tasks.
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Zhipu AI
GLM-4.6 was introduced as an enhanced iteration of the GLM-4 series, designed to provide improved capabilities in bilingual language understanding and generation. Built to incorporate refinements to the GLM architecture, it represents continued advancement in Zhipu AI's model development.
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Meta
Llama 3.2 3B was created as an ultra-compact open-source model, designed to enable on-device and edge deployment scenarios. Built with just 3 billion parameters while retaining instruction-following abilities, it brings Meta's language technology to mobile devices, IoT applications, and resource-constrained environments.
1 year newer
Llama 3.2 3B Instruct
Meta
2024-09-25
GLM-4.6
Zhipu AI
2025-09-30
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Pricing Comparison
Cost per million tokens (USD)
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GLM-4.6
Input:$0.60
Output:$2.00
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Llama 3.2 3B Instruct
Input:$0.01
Output:$0.02($2.57 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GLM-4.6
Average Score:81.0%(+48.2%)
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Llama 3.2 3B Instruct
Average Score:32.8%
Provider Availability & Performance
Available providers and their performance metrics
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GLM-4.6
2 providers
DeepInfra
Throughput: 85 tok/s
Latency: 0.7ms
ZeroEval
Throughput: 85 tok/s
Latency: 0.7ms
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Llama 3.2 3B Instruct
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GLM-4.6
Avg Score:81.0%(+48.2%)
Providers:2
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Llama 3.2 3B Instruct
Avg Score:32.8%
Providers:1