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GPT-3.5 Turbo 16k vs DeepSeek V3.1

Detailed technical comparison between GPT-3.5 Turbo 16k (OpenAI) and DeepSeek V3.1 (DeepSeek). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.

โšก Executive Summary & Verdict

Comparison Snapshot

GPT-3.5 Turbo 16k: 0 WinsvsDeepSeek V3.1: 6 Wins
Context Leader

DeepSeek V3.1

163,840 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

DeepSeek V3.1

$0.25 / MTok
OpenAIactive

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...

View GPT-3.5 Turbo 16k Full Specs โ†’
DeepSeekactive

DeepSeek V3.1

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

View DeepSeek V3.1 Full Specs โ†’

Technical Specifications

๐Ÿ† = Superior Spec
SpecificationGPT-3.5 Turbo 16kDeepSeek V3.1
ProviderOpenAIDeepSeek
Context Window16,385 tokens163,840 tokens๐Ÿ†
Agent SuitabilityNot yet benchmarkedNot yet benchmarked
Time to First Token (TTFT)No public TTFT dataNo public TTFT data
Deployment Modelmanaged apiself hostable
Production StabilityStable GA (est.)Stable GA (est.)
API AvailableYesYes
Released Date2023-08-282025-08-21

API Pricing Comparison

Input Price per Million Tokens

GPT-3.5 Turbo 16k

$3.00

DeepSeek V3.1

$0.25

Output Price per Million Tokens

GPT-3.5 Turbo 16k

$4.00

DeepSeek V3.1

$0.95

๐Ÿ’ก Cost Ratio: DeepSeek V3.1 is 12.0x cheaper per input token than GPT-3.5 Turbo 16k.

Want to test both models live?

Run side-by-side prompt benchmarks in our dynamic multi-model Sandbox. Compare execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Standardized Scores (0โ€“100%)

Scores show verified raw accuracy percentages across standardized AI evaluation suites. Higher bars indicate superior performance in that domain.

MMLUGeneral knowledge & multi-task understanding
79.4%vs80.0%+0.6% DeepSeek V3.1
GPT-3.5 Turbo 16k
DeepSeek V3.1 ๐Ÿ†
HumanEvalPython coding & logic synthesis
77.6%vs78.2%+0.6% DeepSeek V3.1
GPT-3.5 Turbo 16k
DeepSeek V3.1 ๐Ÿ†
MATHComplex mathematical problem solving
54.8%vs55.4%+0.6% DeepSeek V3.1
GPT-3.5 Turbo 16k
DeepSeek V3.1 ๐Ÿ†
GPQAGraduate-level expert reasoning
40.2%vs40.8%+0.6% DeepSeek V3.1
GPT-3.5 Turbo 16k
DeepSeek V3.1 ๐Ÿ†
HellaSwagCommonsense reasoning and inference
82.4%vs83.0%+0.6% DeepSeek V3.1
GPT-3.5 Turbo 16k
DeepSeek V3.1 ๐Ÿ†
MT-BenchMulti-turn conversation flow quality
8.5%vs8.6%+0.1% DeepSeek V3.1
GPT-3.5 Turbo 16k
DeepSeek V3.1 ๐Ÿ†

GPT-3.5 Turbo 16k Quirks & Gotchas

No developer gotchas reported.

DeepSeek V3.1 Quirks & Gotchas

No developer gotchas reported.

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