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GLM-5 vs Together AI - Llama 3 8B Lite

GLM-5 (2026) and Together AI - Llama 3 8B Lite (2025) are frontier reasoning models from Zhipu AI and AI at Meta. GLM-5 ships a 200k-token context window, while Together AI - Llama 3 8B Lite ships a 8K-token context window. On pricing, Together AI - Llama 3 8B Lite costs $0.1/1M input tokens versus $0.72/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Together AI - Llama 3 8B Lite is ~620% cheaper at $0.1/1M; pay for GLM-5 only for reasoning depth.

Specs

Released2026-02-112025-07-15
Context window200k8K
Parameters744B total, 40B active8B
Architecturemixture of expertsdecoder only
LicenseMITOpen Source
Knowledge cutoff-2024-03

Pricing and availability

GLM-5Together AI - Llama 3 8B Lite
Input price$0.72/1M tokens$0.1/1M tokens
Output price$2.3/1M tokens$0.1/1M tokens
Providers

Capabilities

GLM-5Together AI - Llama 3 8B Lite
Vision
Multimodal
Reasoning
Function calling
Tool use
Structured outputs
Code execution

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on reasoning mode: GLM-5. Both models share function calling, tool use, and 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 lists $0.72/1M input and $2.3/1M output tokens, while Together AI - Llama 3 8B Lite lists $0.1/1M input and $0.1/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Together AI - Llama 3 8B Lite lower by about $1.09 per million blended tokens. Availability is 5 providers versus 1, so concentration risk also matters.

Choose GLM-5 when reasoning depth, larger context windows, and broader provider choice are central to the workload. Choose Together AI - Llama 3 8B Lite when provider fit and lower input-token cost 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 or Together AI - Llama 3 8B Lite?

GLM-5 supports 200k tokens, while Together AI - Llama 3 8B Lite supports 8K 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 or Together AI - Llama 3 8B Lite?

Together AI - Llama 3 8B Lite is cheaper on tracked token pricing. GLM-5 costs $0.72/1M input and $2.3/1M output tokens. Together AI - Llama 3 8B Lite costs $0.1/1M input and $0.1/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GLM-5 or Together AI - Llama 3 8B Lite open source?

GLM-5 is listed under MIT. Together AI - Llama 3 8B Lite is listed under Open Source. 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 or Together AI - Llama 3 8B Lite?

GLM-5 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 or Together AI - Llama 3 8B Lite?

Both GLM-5 and Together AI - Llama 3 8B Lite expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Where can I run GLM-5 and Together AI - Llama 3 8B Lite?

GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Together AI - Llama 3 8B Lite is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.