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Claude Opus 4.7 vs R1 Distill Llama 70B

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Claude Opus 4.7 and R1 Distill Llama 70B.

Anthropic

Claude Opus 4.7

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

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DeepSeek

R1 Distill Llama 70B

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...

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Technical Specifications

SpecificationClaude Opus 4.7R1 Distill Llama 70B
ProviderAnthropicDeepSeek
Context Window1,000,000 tokens128,000 tokens
Agent Suitability96/100N/A
Time to First Token (TTFT)480 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-162025-01-23

API Pricing Comparison

Input Price per Million Tokens

Claude Opus 4.7

$5.00

R1 Distill Llama 70B

$0.80

Output Price per Million Tokens

Claude Opus 4.7

$25.00

R1 Distill Llama 70B

$0.80

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
9410.0%vs8520.0%
Claude Opus 4.7
R1 Distill Llama 70B
HumanEvalPython coding & logic synthesis
9610.0%vs8830.0%
Claude Opus 4.7
R1 Distill Llama 70B
MATHComplex mathematical problem solving
9150.0%vs7000.0%
Claude Opus 4.7
R1 Distill Llama 70B
GPQAGraduate-level expert reasoning
8420.0%vs4450.0%
Claude Opus 4.7
R1 Distill Llama 70B
HellaSwagCommonsense reasoning and inference
9880.0%vs8600.0%
Claude Opus 4.7
R1 Distill Llama 70B
MT-BenchMulti-turn conversation flow quality
975.0%vs905.0%
Claude Opus 4.7
R1 Distill Llama 70B

Claude Opus 4.7 Quirks & Gotchas

  • โ–ธTop-tier agentic coding model โ€” excels at autonomous software engineering
  • โ–ธRequires explicit tool_choice parameter for parallel function calling to work reliably

R1 Distill Llama 70B Quirks & Gotchas

No developer gotchas reported.