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Qwen 3.5 vs DeepSeek V4

Comprehensive comparison between Alibaba (Qwen)'s Qwen 3.5 and DeepSeek's DeepSeek V4. Compare pricing, performance, features, and user reviews.

qwen vs deepseekqwen 3.5 vs deepseek v4chinese open source ai

Qwen 3.5

Alibaba (Qwen)

Alibaba's flagship open-source MoE model with 397B total parameters (17B active per pass). Apache 2.0 licensed for commercial use. Supports 201 languages with native vision capabilities. Best open-weight model for local deployment.

$0.39/$1.56per M tokens
Details

DeepSeek V4

DeepSeek

DeepSeek V4 (released 2026-04-24) ships two MIT-licensed MoE variants: V4-Pro (1.6T/49B active) and V4-Flash (284B/13B active), both with 1M-token context and hybrid Compressed Sparse Attention + Heavily Compressed Attention. Three reasoning modes (Non-think / Think High / Think Max). V4-Pro uses only 27% of V3.2's FLOPs and 10% of its KV cache at 1M context. Priced well below GPT-5.5 / Opus 4.7 while matching them on most benchmarks.

$1.74/$3.48per M tokens
Details

Specs Comparison

SpecificationQwen 3.5DeepSeek V4
Context Window262K1000K
Max Output32K66K
Input (per 1M tokens)$0.39$1.74
Output (per 1M tokens)$1.56$3.48
Reasoning
Open Source

Scenario Score Comparison

Coding
87
vs
—
Writing
82
vs
—

Qwen 3.5

Pros

  • + Open source (Apache 2.0)
  • + Self-hostable with vLLM
  • + 201 language support
  • + MoE efficiency (17B active)
  • + Cheapest API among frontier-class
  • + Strong vision/multimodal performance

Cons

  • − Weaker on hard coding tasks vs Opus/GPT
  • − Requires significant VRAM for local hosting
  • − Quantization affects complex reasoning
  • − Smaller context than GPT-5.4/Opus 4.6

DeepSeek V4

Pros

  • + 1M token context window with aggressive KV-cache compression
  • + MIT license — fully open-source, self-hostable
  • + V4-Pro $1.74/$3.48 per MTok — far cheaper than GPT-5.5 and Opus 4.7
  • + New SOTA for open models on SimpleQA-Verified (57.9)
  • + OpenAI + Anthropic API-compatible endpoints
  • + Three reasoning modes tunable per request

Cons

  • − Still trails GPT-5.4 / Gemini 3.1 Pro by 3-6 months on frontier benchmarks
  • − Servers in China (overseas latency, geopolitical concerns)
  • − Text-only — V3's multimodal (image/video) capability not confirmed for V4
  • − V4-Pro self-hosting needs substantial hardware (49B active × FP4/FP8)

Recommendation

Choose Qwen 3.5 if you:

  • • Need open source (apache 2.0)
  • • Need self-hostable with vllm
  • • Need 201 language support

Choose DeepSeek V4 if you:

  • • Need 1m token context window with aggressive kv-cache compression
  • • Need mit license — fully open-source, self-hostable
  • • Need v4-pro $1.74/$3.48 per mtok — far cheaper than gpt-5.5 and opus 4.7

Based on scores across 2 scenarios, Qwen 3.5 performs better overall.

Qwen 3.5 Details DeepSeek V4 Details

Get Started with Qwen 3.5

1Visit the provider's website
2Create an account
3Start using the model

Get Started with DeepSeek V4

1Visit the provider's website
2Create an account
3Start using the model

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