GLM-5.1 vs Llama 3.2 1B Instruct

Name: GLM-5.1
Author: Zhipu AI

GLM-5.1 (2026) and Llama 3.2 1B Instruct (2024) are frontier reasoning models from Zhipu AI and AI at Meta. GLM-5.1 ships a 200k-token context window, while Llama 3.2 1B Instruct ships a 128k-token context window. On Google-Proof Q&A, GLM-5.1 leads by 60.6 pts. On pricing, Llama 3.2 1B Instruct costs $0.03/1M input tokens versus $1.05/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Llama 3.2 1B Instruct is ~3789% cheaper at $0.03/1M; pay for GLM-5.1 only for coding workflow support.

Decision scorecard

Local evidence first

Signal	GLM-5.1	Llama 3.2 1B Instruct	How to read it
Best for	reasoning-heavy apps, tool-calling agents, and provider-routed production	provider-routed production	Use-case synthesis from product type, capability flags, context, and provider data.
Decision fit	Coding, RAG, and Agents	Coding, RAG, and Long context	Primary workload tags from local decision data.
Context window	200k	128k	Higher is better when prompts, retrieval chunks, or transcripts are large.
Cheapest output	$3.50/1M tokens	$0.20/1M tokens	Cheapest tracked provider route; verify your exact region and tier.
Provider routes	5 tracked	7 tracked	Broader coverage can reduce vendor lock-in and fallback risk.
Shared benchmarks	Google-Proof Q&A leader	1 shared	Visible benchmark lead is 60.6 points on Google-Proof Q&A.

Decision tradeoffs

Choose GLM-5.1 when...

GLM-5.1 holds a shared-benchmark lead on Google-Proof Q&A, ahead by 60.6 points.
GLM-5.1 has the larger context window for long prompts, retrieval packs, or transcript analysis.
GLM-5.1 uniquely exposes Reasoning, JSON / Tool use, and Code execution in local model data.
Local decision data tags GLM-5.1 for Coding, RAG, and Agents.

Choose Llama 3.2 1B Instruct when...

Llama 3.2 1B Instruct has the lower cheapest tracked output price at $0.20/1M tokens.
Llama 3.2 1B Instruct has broader tracked provider coverage for fallback and route flexibility.
Local decision data tags Llama 3.2 1B Instruct for Coding, RAG, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Llama 3.2 1B Instruct

Requests / monthInput tokens / requestOutput tokens / request

GLM-5.1

$1,715

Cheapest tracked route/tier: OpenRouter

Llama 3.2 1B Instruct

$71.85

Cheapest tracked route/tier: Cloudflare Workers AI

Estimated monthly gap: $1,643. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GLM-5.1 -> Llama 3.2 1B Instruct

Provider overlap exists on OpenRouter, Fireworks AI, and Vercel AI Gateway; start route-level A/B tests there.
Llama 3.2 1B Instruct is $3.30/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Check replacement coverage for Reasoning, JSON / Tool use, and Code execution before moving production traffic.

Llama 3.2 1B Instruct -> GLM-5.1

Provider overlap exists on OpenRouter, Fireworks AI, and Vercel AI Gateway; start route-level A/B tests there.
GLM-5.1 is $3.30/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
GLM-5.1 adds Reasoning, JSON / Tool use, and Code execution in local capability data.

Specs

Specification	GLM-5.1 Zhipu AI	Llama 3.2 1B Instruct AI at Meta
Released	2026-04-07	2024-09-25
Context window	200k	128k
Parameters	754B total, 40B active	1.23B
Architecture	Mixture of Experts	Decoder Only
License	MITOSI-approved	Llama 3 Community
Openness	Open source	Open weights
Weights	Available	Unknown
Code	Unknown	Unknown
Commercial use	Commercial use: permitted	Commercial use: conditional
Knowledge cutoff	2025-11	2023-12

Pricing and availability

Pricing attribute	GLM-5.1	Llama 3.2 1B Instruct
Input price	$1.05/1M tokens	$0.03/1M tokens
Output price	$3.50/1M tokens	$0.20/1M tokens
Providers	Z.ai OpenRouter Fireworks AI Vercel AI Gateway Novita AI	Cloudflare Workers AI OpenRouter Fireworks AI NVIDIA NIM Bitdeer AI AWS Bedrock

Capabilities

Capability	GLM-5.1	Llama 3.2 1B Instruct
Vision	No	No
Multimodal	No	No
Reasoning	Yes	No
JSON / Tool use	Yes	No
Structured outputs	Yes	Yes
Code execution	Yes	No
IDE integration	No	No
Computer use	No	No
Parallel agents	No	No

Benchmarks

Benchmark	GLM-5.1	Llama 3.2 1B Instruct
Google-Proof Q&A	86.2	25.6

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Model pages

Labs and families

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Last reviewed: 2026-07-09. Data sourced from public model cards and provider documentation.

Both models

GLM-5.1 Llama 3.2 1B Instruct