Grok 4.20 vs Llama 3 70B Instruct
Grok 4.20 (2026) and Llama 3 70B Instruct (2024) are frontier reasoning models from xAI and AI at Meta. Grok 4.20 ships a 2M-token context window, while Llama 3 70B Instruct ships a 8K-token context window. On pricing, Llama 3 70B Instruct costs $0.4/1M input tokens versus $4.2/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3 70B Instruct is ~950% cheaper at $0.4/1M; pay for Grok 4.20 only for reasoning depth.
Specs
| Released | 2026-01-01 | 2024-04-18 |
| Context window | 2M | 8K |
| Parameters | — | 70B |
| Architecture | - | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Grok 4.20 | Llama 3 70B Instruct | |
|---|---|---|
| Input price | $4.2/1M tokens | $0.4/1M tokens |
| Output price | $12.60/1M tokens | $0.4/1M tokens |
| Providers |
Capabilities
| Grok 4.20 | Llama 3 70B Instruct | |
|---|---|---|
| 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: Grok 4.20, function calling: Grok 4.20, and tool use: Grok 4.20. 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 4.20 lists $4.2/1M input and $12.60/1M output tokens, while Llama 3 70B Instruct lists $0.4/1M input and $0.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 70B Instruct lower by about $6.32 per million blended tokens. Availability is 1 providers versus 18, so concentration risk also matters.
Choose Grok 4.20 when reasoning depth and larger context windows are central to the workload. Choose Llama 3 70B Instruct when provider fit, lower input-token cost, 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, Grok 4.20 or Llama 3 70B Instruct?
Grok 4.20 supports 2M tokens, while Llama 3 70B Instruct 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, Grok 4.20 or Llama 3 70B Instruct?
Llama 3 70B Instruct is cheaper on tracked token pricing. Grok 4.20 costs $4.2/1M input and $12.60/1M output tokens. Llama 3 70B Instruct costs $0.4/1M input and $0.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Grok 4.20 or Llama 3 70B Instruct open source?
Grok 4.20 is listed under Proprietary. Llama 3 70B Instruct 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, Grok 4.20 or Llama 3 70B Instruct?
Grok 4.20 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, Grok 4.20 or Llama 3 70B Instruct?
Grok 4.20 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 Grok 4.20 and Llama 3 70B Instruct?
Grok 4.20 is available on xAI Console. Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. 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.