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DeepSeek R1 vs GPT-3.5 Turbo 16k

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 R1 and GPT-3.5 Turbo 16k.

DeepSeek

DeepSeek R1

A premier reasoning model employing large-scale reinforcement learning. Displays specialized math, coding, and logical validation capabilities comparable to OpenAI's o1.

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OpenAI

GPT-3.5 Turbo 16k

This model offers four times the context length of gpt-3.5-turbo, allowing it to support approximately 20 pages of text in a single request at a higher cost. Training data: up...

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Technical Specifications

SpecificationDeepSeek R1GPT-3.5 Turbo 16k
ProviderDeepSeekOpenAI
Context Window163,840 tokens16,385 tokens
Agent Suitability78/100N/A
Time to First Token (TTFT)1800 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-01-202023-08-28

API Pricing Comparison

Input Price per Million Tokens

DeepSeek R1

$0.70

GPT-3.5 Turbo 16k

$3.00

Output Price per Million Tokens

DeepSeek R1

$2.50

GPT-3.5 Turbo 16k

$4.00

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
9080.0%vsN/A
DeepSeek R1
GPT-3.5 Turbo 16k
HumanEvalPython coding & logic synthesis
9280.0%vsN/A
DeepSeek R1
GPT-3.5 Turbo 16k
MATHComplex mathematical problem solving
9310.0%vsN/A
DeepSeek R1
GPT-3.5 Turbo 16k
GPQAGraduate-level expert reasoning
6210.0%vsN/A
DeepSeek R1
GPT-3.5 Turbo 16k
HellaSwagCommonsense reasoning and inference
9050.0%vsN/A
DeepSeek R1
GPT-3.5 Turbo 16k
MT-BenchMulti-turn conversation flow quality
935.0%vsN/A
DeepSeek R1
GPT-3.5 Turbo 16k

DeepSeek R1 Quirks & Gotchas

  • โ–ธReasoning model โ€” not designed for high-frequency tool calling
  • โ–ธPair with a smaller model (V4 Flash) for routing and use R1 for complex reasoning only

GPT-3.5 Turbo 16k Quirks & Gotchas

No developer gotchas reported.