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DeepSeek V4 Pro 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 DeepSeek V4 Pro and R1 Distill Llama 70B.

DeepSeek

DeepSeek V4 Pro

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...

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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

SpecificationDeepSeek V4 ProR1 Distill Llama 70B
ProviderDeepSeekDeepSeek
Context Window1,048,576 tokens128,000 tokens
Agent Suitability94/100N/A
Time to First Token (TTFT)280 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-242025-01-23

API Pricing Comparison

Input Price per Million Tokens

DeepSeek V4 Pro

$0.43

R1 Distill Llama 70B

$0.80

Output Price per Million Tokens

DeepSeek V4 Pro

$0.87

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
8850.0%vs8520.0%
DeepSeek V4 Pro
R1 Distill Llama 70B
HumanEvalPython coding & logic synthesis
8900.0%vs8830.0%
DeepSeek V4 Pro
R1 Distill Llama 70B
MATHComplex mathematical problem solving
7460.0%vs7000.0%
DeepSeek V4 Pro
R1 Distill Llama 70B
GPQAGraduate-level expert reasoning
4900.0%vs4450.0%
DeepSeek V4 Pro
R1 Distill Llama 70B
HellaSwagCommonsense reasoning and inference
8750.0%vs8600.0%
DeepSeek V4 Pro
R1 Distill Llama 70B
MT-BenchMulti-turn conversation flow quality
918.0%vs905.0%
DeepSeek V4 Pro
R1 Distill Llama 70B

DeepSeek V4 Pro Quirks & Gotchas

  • โ–ธMoE architecture โ€” cold-start latency on first request, use keep-alive
  • โ–ธBest cost-performance ratio of any frontier model โ€” strong tool calling for agentic use

R1 Distill Llama 70B Quirks & Gotchas

No developer gotchas reported.