Grok Code Fast 1 vs Llama 2 70B Chat
Grok Code Fast 1 (2025) and Llama 2 70B Chat (2023) are agentic coding models from xAI and AI at Meta. Grok Code Fast 1 ships a 262K-token context window, while Llama 2 70B Chat ships a 4K-token context window. On pricing, Grok Code Fast 1 costs $0.2/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Grok Code Fast 1 is ~150% cheaper at $0.2/1M; pay for Llama 2 70B Chat only for provider fit.
Specs
| Released | 2025-08-27 | 2023-07-18 |
| Context window | 262K | 4K |
| Parameters | 314B | 70B |
| Architecture | mixture of experts | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Grok Code Fast 1 | Llama 2 70B Chat | |
|---|---|---|
| Input price | $0.2/1M tokens | $0.5/1M tokens |
| Output price | $1.5/1M tokens | $1.5/1M tokens |
| Providers |
Capabilities
| Grok Code Fast 1 | Llama 2 70B Chat | |
|---|---|---|
| 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 function calling: Grok Code Fast 1 and tool use: Grok Code Fast 1. 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, Grok Code Fast 1 lists $0.2/1M input and $1.5/1M output tokens, while Llama 2 70B Chat lists $0.5/1M input and $1.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Grok Code Fast 1 lower by about $0.21 per million blended tokens. Availability is 1 providers versus 14, so concentration risk also matters.
Choose Grok Code Fast 1 when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose Llama 2 70B Chat 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.
FAQ
Which has a larger context window, Grok Code Fast 1 or Llama 2 70B Chat?
Grok Code Fast 1 supports 262K tokens, while Llama 2 70B Chat supports 4K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Grok Code Fast 1 or Llama 2 70B Chat?
Grok Code Fast 1 is cheaper on tracked token pricing. Grok Code Fast 1 costs $0.2/1M input and $1.5/1M output tokens. Llama 2 70B Chat costs $0.5/1M input and $1.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Grok Code Fast 1 or Llama 2 70B Chat open source?
Grok Code Fast 1 is listed under Proprietary. Llama 2 70B Chat 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 function calling, Grok Code Fast 1 or Llama 2 70B Chat?
Grok Code Fast 1 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.
Which is better for tool use, Grok Code Fast 1 or Llama 2 70B Chat?
Grok Code Fast 1 has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Grok Code Fast 1 and Llama 2 70B Chat?
Grok Code Fast 1 is available on OpenRouter. Llama 2 70B Chat is available on Databricks Foundation Model Serving, Microsoft Foundry, GCP Vertex AI, Alibaba Cloud PAI-EAS, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.