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DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across...
Verified scores from SWE-bench and Artificial Analysis.
Resolving real-world GitHub issues end-to-end without human intervention
Estimate production API costs for R1 Distill Llama 70B.
Verified ratings across 4 core software engineering dimensions.
Refactoring accuracy, syntax correctness, and adherence to design patterns.
Zero hallucinations, strict constraint compliance, and negative prompt respect.
Time-to-first-token (TTFT) and throughput tokens per second.
Token pricing economics relative to intelligence quality and output volume.
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Master React Server Components, Server Actions, parallel routes, streaming, ISR, and cache revalidation.
Write idiomatic React 19 using useActionState, useOptimistic, Actions, ref-as-prop, and React Compiler idioms.
Design type-safe database schemas, execute optimized relational queries, and manage migrations across SQLite, Postgres, and D1.
R1 Distill Llama 70B costs $0.80 per 1M input tokens and $0.80 per 1M output tokens.
No. R1 Distill Llama 70B is not listed with tool calling support, so it is a poor fit for agents that need to call tools or MCP servers.
R1 Distill Llama 70B has a 8,192-token context window and can generate up to 7,372 tokens in one response.
Based on its capabilities, R1 Distill Llama 70B is a good match for Next.js 15 App Router Expert, React 19 Core Patterns, Drizzle ORM Specialist.