GLM-5 vs Llama 3.2 1B Instruct
GLM-5 (2026) and Llama 3.2 1B Instruct (2024) are frontier reasoning models from Zhipu AI and AI at Meta. GLM-5 ships a 200k-token context window, while Llama 3.2 1B Instruct ships a 128k-token context window. On MMLU PRO, GLM-5 leads by 66 pts. On pricing, Llama 3.2 1B Instruct costs $0.03/1M input tokens versus $0.60/1M 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 ~2122% cheaper at $0.03/1M; pay for GLM-5 only for reasoning depth.
Decision scorecard
Local evidence first| Signal | GLM-5 | Llama 3.2 1B Instruct |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Long context |
| Context window | 200k | 128k |
| Cheapest output | $2.08/1M tokens | $0.20/1M tokens |
| Provider routes | 7 tracked | 7 tracked |
| Shared benchmarks | MMLU PRO leader | 2 shared |
Decision tradeoffs
- GLM-5 holds a shared-benchmark lead on MMLU PRO, ahead by 66 points.
- GLM-5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5 uniquely exposes Reasoning and JSON / Tool use in local model data.
- Local decision data tags GLM-5 for Coding, RAG, and Agents.
- Llama 3.2 1B Instruct has the lower cheapest tracked output price at $0.20/1M tokens.
- 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.
GLM-5
$1,000
Cheapest tracked route/tier: OpenRouter
Llama 3.2 1B Instruct
$71.85
Cheapest tracked route/tier: Cloudflare Workers AI
Estimated monthly gap: $928. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter, Fireworks AI, and NVIDIA NIM; start route-level A/B tests there.
- Llama 3.2 1B Instruct is $1.88/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning and JSON / Tool use before moving production traffic.
- Provider overlap exists on Fireworks AI, OpenRouter, and NVIDIA NIM; start route-level A/B tests there.
- GLM-5 is $1.88/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GLM-5 adds Reasoning and JSON / Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-11 | 2024-09-25 |
| Context window | 200k | 128k |
| Parameters | 744B 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 | Llama 3.2 1B Instruct |
|---|---|---|
| Input price | $0.60/1M tokens | $0.03/1M tokens |
| Output price | $2.08/1M tokens | $0.20/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5 | 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 | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GLM-5 | Llama 3.2 1B Instruct |
|---|---|---|
| MMLU PRO | 86.0 | 20.0 |
| Google-Proof Q&A | 86.0 | 25.6 |
Continue comparing
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Last reviewed: 2026-07-09. Data sourced from public model cards and provider documentation.