GLM-5 vs Llama 3 70B Instruct
GLM-5 (2026) and Llama 3 70B Instruct (2024) are frontier reasoning models from Zhipu AI and AI at Meta. GLM-5 ships a 200k-token context window, while Llama 3 70B Instruct ships a 8k-token context window. On MMLU PRO, GLM-5 leads by 28.6 pts. On pricing, Llama 3 70B Instruct costs $0.40/1M 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 70B Instruct is ~50% cheaper at $0.40/1M; pay for GLM-5 only for reasoning depth.
Decision scorecard
Local evidence first| Signal | GLM-5 | Llama 3 70B Instruct |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, Classification, and JSON / Tool use |
| Context window | 200k | 8k |
| Cheapest output | $2.08/1M tokens | $0.40/1M tokens |
| Provider routes | 7 tracked | 18 tracked |
| Shared benchmarks | MMLU PRO leader | 1 shared |
Decision tradeoffs
- GLM-5 holds a shared-benchmark lead on MMLU PRO, ahead by 28.6 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 70B Instruct has the lower cheapest tracked output price at $0.40/1M tokens.
- Llama 3 70B Instruct has broader tracked provider coverage for fallback and route flexibility.
- Local decision data tags Llama 3 70B Instruct for Coding, Classification, and JSON / Tool use.
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 70B Instruct
$420
Cheapest tracked route/tier: Hyperbolic AI Inference
Estimated monthly gap: $580. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on GCP Vertex AI, NVIDIA NIM, and Fireworks AI; start route-level A/B tests there.
- Llama 3 70B Instruct is $1.68/1M 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 Together AI; start route-level A/B tests there.
- GLM-5 is $1.68/1M 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 | 2024-04-18 |
| Context window | 200k | 8k |
| Parameters | 744B total, 40B active | 70B |
| Architecture | Mixture of Experts | Decoder Only |
| License | MITOSI-approved | Llama 3 Community |
| Openness | Open source | Open weights |
| Weights | Available | Available |
| 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 70B Instruct |
|---|---|---|
| Input price | $0.60/1M tokens | $0.40/1M tokens |
| Output price | $2.08/1M tokens | $0.40/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5 | Llama 3 70B 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 70B Instruct |
|---|---|---|
| MMLU PRO | 86.0 | 57.4 |
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Last reviewed: 2026-07-11. Data sourced from public model cards and provider documentation.