SSyncDev

AI model comparison

Qwen Turbo vs DeepSeek V4 Flash 0731

Compare recorded price, context, output limits, speed, latency, capabilities, and input/output support. Every missing value stays visible, and unsourced benchmarks are excluded.

Qwen Turbo and DeepSeek V4 Flash 0731 both come up when teams are choosing a model for production work, and the honest answer usually depends on your workload rather than a leaderboard. This page puts their published specifications side by side — context window, token pricing, supported inputs and outputs — so you can see where they actually differ.

Side-by-sideReviewed by our team

Alibaba

Qwen Turbo

Efficient Qwen model for fast chat, extraction, and high-volume workloads

Context
1M
Max output
16.4K
Input / 1M
$0.05
Output / 1M
$0.20
Output speed
—

Accepts

  • Text input

Produces

  • Text output
Full model profileVendor docs ↗
VS

DeepSeek

DeepSeek V4 Flash 0731

Official DeepSeek V4 Flash release with enhanced agentic capabilities and integrated DSpark speculative decoding

Context
1M
Max output
384K
Input / 1M
$0.16
Output / 1M
$0.40
Output speed
—

Accepts

  • Text input

Produces

  • Text output
Full model profileVendor docs ↗

At a glance

Decision snapshot

This is a directional summary of the values recorded in this directory—not a universal quality verdict. Test the finalists on your own prompts before committing.

Where Qwen Turbo leads in recorded data

  • Input price: $0.05
  • Output price: $0.20

Where DeepSeek V4 Flash 0731 leads in recorded data

  • Maximum output: 384K

Context capacity

Higher listed limit

Qwen Turbo:1M

DeepSeek V4 Flash 0731:1M

Same recorded value

Maximum output

Higher listed limit

Qwen Turbo:16.4K

DeepSeek V4 Flash 0731:384K

DeepSeek V4 Flash 0731

Input price

Lower recorded price

Qwen Turbo:$0.05

DeepSeek V4 Flash 0731:$0.16

Qwen Turbo

Output price

Lower recorded price

Qwen Turbo:$0.20

DeepSeek V4 Flash 0731:$0.40

Qwen Turbo

Output speed

Higher recorded throughput

Qwen Turbo:—

DeepSeek V4 Flash 0731:—

No complete comparison

Time to first token

Lower recorded latency

Qwen Turbo:—

DeepSeek V4 Flash 0731:—

No complete comparison

Intelligence Index

Higher directory index

Qwen Turbo:—

DeepSeek V4 Flash 0731:—

No complete comparison

Evidence

Verified shared benchmarks

A score appears only when both records include a verified source. It is not treated as a universal ranking.

These two models haven't been measured on the same benchmark yet, so there's nothing meaningful to chart. Comparing scores from different tests would tell you more about the tests than the models — the specs and pricing above are the better guide here.

Specifications

Pricing, limits and capabilities

SpecificationQwen TurboDeepSeek V4 Flash 0731
ProviderAlibabaDeepSeek
Model familyqwendeepseek-flash
Accepted inputstexttext
Produced outputstexttext
Context window1M1M
Max output16.4K384KRecorded lead
Intelligence Index——
Input price / 1M$0.05Recorded lead$0.16
Output price / 1M$0.20Recorded lead$0.40
Output speed——
Time to first token——
Reasoning modeDocumentedDocumented
Tool callingDocumentedDocumented
Image inputNot documentedNot documented
Audio inputNot documentedNot documented
Structured outputNot documentedDocumented
LicenseProprietaryOpen weights
ReleasedNov 1, 2024Jul 31, 2026

Workload guidance

Which model should you choose?

On the published numbers, DeepSeek V4 Flash 0731 accepts the larger context window and Qwen Turbo is cheaper per input token. Which matters more depends on whether your bottleneck is document size or spend — the table above has the exact figures.

Provenance

Sources and data limits

Prices and hosted performance can change. SyncDev records source references and clearly separates documented specifications from measured values; confirm commercial terms with the provider before deployment.

Questions people ask

It compares recorded context and output limits, token prices, output speed, time to first token, Intelligence Index, modality support, tool and structured-output capabilities, release information, and only source-linked benchmarks verified on both records. Missing information is labeled rather than inferred.

Compare a different pair

Choose any two approved model records and review them with the same evidence rules.

Open model comparison