DeepSeek V4 Flash 0423 is DeepSeek's efficiency-optimized Mixture-of-Experts text model, designed for fast inference and workflows requiring tool use, function calling, and structured outputs. It features 284B total parameters with 13B activated parameters and supports a 1M-token context window with cost-effective pricing.
DeepSeek V4 Flash vs Qwen3 235B A22B Thinking 2507
Compare DeepSeek V4 Flash from DeepSeek and Qwen3 235B A22B Thinking 2507 from Qwen on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
The open-source thinking model based on Qwen3 has significantly improved in logical ability, general capability, knowledge enhancement, and creative ability compared to the previous version (Tongyi Qianwen 3-235B-A22B). It is suitable for high-difficulty and strong reasoning scenarios.
Pricing & Specifications
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
Promotional prices show the discounted rate; see each model page for promotion windows.
Activity Past 30 Days
Daily traffic served through AIHubMix — how demand for each model is trending.
Tokens / day
Requests / day
Performance Past 3 Days
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Throughput (tok/s)
TTFT (s)
Uptime (%)
LMArena Benchmarks
LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.
Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.
Cost calculator
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
FAQ
Which is cheaper: DeepSeek V4 Flash, Qwen3 235B A22B Thinking 2507?
DeepSeek V4 Flash: $0.928/M output tokens; Qwen3 235B A22B Thinking 2507: $2.8/M. Use the cost calculator above to estimate your own workload.
How do their coding arena scores compare?
DeepSeek V4 Flash: 1452; Qwen3 235B A22B Thinking 2507: 1424 (LMArena coding leaderboard).
Which responds faster?
Qwen3 235B A22B Thinking 2507: 0.3s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
Which one generates tokens faster?
Qwen3 235B A22B Thinking 2507 at 87.4 tok/s and DeepSeek V4 Flash at 59.0 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
What inputs and capabilities does each model support?
DeepSeek V4 Flash accepts text input and supports tool calling, function calling and structured outputs; Qwen3 235B A22B Thinking 2507 accepts text and image input and supports thinking, tool calling, function calling and structured outputs.
Can I call DeepSeek V4 Flash and Qwen3 235B A22B Thinking 2507 with the same API key?
Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.
Popular comparisons
Related model match-ups readers also look at.