GLM-5 Turbo vs Llama 3.1 405B Instruct
GLM-5 Turbo (2026) and Llama 3.1 405B Instruct (2024) are frontier reasoning models from Zhipu AI and AI at Meta. GLM-5 Turbo ships a 200k-token context window, while Llama 3.1 405B Instruct ships a 128k-token context window. On pricing, GLM-5 Turbo costs $1.20/1M input tokens versus $2.40/1M 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.
GLM-5 Turbo is ~100% cheaper at $1.20/1M; pay for Llama 3.1 405B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | GLM-5 Turbo | Llama 3.1 405B Instruct |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | provider-routed production |
| Decision fit | RAG, Agents, and Long context | RAG, Long context, and Classification |
| Context window | 200k | 128k |
| Cheapest output | $4/1M tokens | $2.40/1M tokens |
| Provider routes | 2 tracked | 11 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GLM-5 Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5 Turbo uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GLM-5 Turbo for RAG, Agents, and Long context.
- Llama 3.1 405B Instruct has the lower cheapest tracked output price at $2.40/1M tokens.
- Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3.1 405B Instruct for RAG, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GLM-5 Turbo
$1,960
Cheapest tracked route/tier: OpenRouter
Llama 3.1 405B Instruct
$2,520
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $560. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for GLM-5 Turbo and Llama 3.1 405B Instruct; plan for SDK, billing, or endpoint changes.
- Llama 3.1 405B Instruct is $1.60/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- No overlapping tracked provider route is sourced for Llama 3.1 405B Instruct and GLM-5 Turbo; plan for SDK, billing, or endpoint changes.
- GLM-5 Turbo is $1.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GLM-5 Turbo adds Reasoning, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-01 | 2024-07-23 |
| Context window | 200k | 128k |
| Parameters | 744B total, 40B active | 405B |
| Architecture | mixture of experts | decoder only |
| License | MIT(OSI) | Llama 3 Community |
| Openness | Open source | Open weights |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | 2025-11 | 2023-12 |
Pricing and availability
| Pricing attribute | GLM-5 Turbo | Llama 3.1 405B Instruct |
|---|---|---|
| Input price | $1.20/1M tokens | $2.40/1M tokens |
| Output price | $4/1M tokens | $2.40/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5 Turbo | Llama 3.1 405B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| 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
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: GLM-5 Turbo, function calling: GLM-5 Turbo, and tool use: GLM-5 Turbo. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GLM-5 Turbo lists $1.20/1M input and $4/1M output tokens on the cheapest tracked provider, while Llama 3.1 405B Instruct lists $2.40/1M input and $2.40/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GLM-5 Turbo lower by about $0.36 per million blended tokens. Availability is 2 providers versus 11, so concentration risk also matters.
Choose GLM-5 Turbo when reasoning depth, larger context windows, and lower input-token cost are central to the workload. Choose Llama 3.1 405B Instruct when provider fit and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, GLM-5 Turbo or Llama 3.1 405B Instruct?
GLM-5 Turbo supports 200k tokens, while Llama 3.1 405B Instruct supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, GLM-5 Turbo or Llama 3.1 405B Instruct?
GLM-5 Turbo is cheaper on tracked token pricing. GLM-5 Turbo costs $1.20/1M input and $4/1M output tokens. Llama 3.1 405B Instruct costs $2.40/1M input and $2.40/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5 Turbo or Llama 3.1 405B Instruct open source?
GLM-5 Turbo is listed under MIT. Llama 3.1 405B Instruct is listed under Llama 3 Community. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for reasoning mode, GLM-5 Turbo or Llama 3.1 405B Instruct?
GLM-5 Turbo has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, GLM-5 Turbo or Llama 3.1 405B Instruct?
GLM-5 Turbo has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GLM-5 Turbo and Llama 3.1 405B Instruct?
GLM-5 Turbo is available on OpenRouter and Vercel AI Gateway. Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.