--- title: "Qwen: Qwen3.5-Flash — price, capability and what beats it · Undominated.ai" canonical: https://undominated.ai/models/qwen__qwen3.5-flash-02-23/ description: "Qwen: Qwen3.5-Flash: $0.065/M in, $0.260/M out. Independent capability scores, and alternatives compared under recorded workload and capability requirements." --- # Qwen: Qwen3.5-Flash — price, capability and what beats it · Undominated.ai > Qwen: Qwen3.5-Flash: $0.065/M in, $0.260/M out. Independent capability scores, and alternatives compared under recorded workload and capability requirements. [Check base rates for this workload](/check/qwen__qwen3.5-flash-02-23/) [Cheaper alternatives](/alternatives/qwen__qwen3.5-flash-02-23/) [Family](/families/qwen/) [Compare models](https://undominated.ai/compare/?models=qwen%2Fqwen3.5-flash-02-23) Comparison context Choose up to three standard models in Compare. Requirements and prompt length apply in Compare. This page keeps its stated price basis and workload controls. MODEL PROOF # Qwen3.5-Flash Qwen · 25 Feb 2026 Balanced Summarise Chat Code gen Agentic TRADE-OFF ## A stored alternative has an equal-or-higher score and an equal-or-lower price, with capability losses. **$0.114** / 1M tokens Balanced · 3 tokens in per 1 out [DeepSeek V4 Flash 0423](/models/deepseek__deepseek-v4-flash/) · Δ score 35.1 points · 1% lower measured price - no image, video input Evidence as of 06 Oct 2026 [openrouter/models](https://openrouter.ai/api/v1/models) [LMArena · cc-by-4.0](https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset) Independent LMArena score 1,397 ± 3.65 · 61,669 votes Context window 1M Maximum output 65.54K Input modalities text, image, video Output modalities text Published input price $0.065 / 1M tokens Published output price $0.260 / 1M tokens Pricing kind fixed Inspect [complete billing conditions](#billing-details) and endpoint terms below. Price from Alibaba: the cheapest offer that is serving, at standard delivery and at the maker’s precision or better, at its standard rate. Every price dimension · USD per million tokens | Input | $0.065 /M | | --- | --- | | Output | $0.260 /M | | Cached input | Unknown /M | | Cache write | Unknown /M | | Cache write 1h | Unknown /M | | Reasoning | Unknown /M | ### Who sells it The same weights, different shops. Cheapest is not like-for-like when serving precision differs. 1 provider offers · rates, limits and conditions Rates are USD per million tokens. Endpoint terms can differ even when the quoted price and precision match. A listed parameter is a provider declaration, not a task-success test. | Seller | Input | Output | Precision | Uptime (1d) | | --- | --- | --- | --- | --- | | Seller Alibaba alibaba Endpoint terms Cached input /M Unknown Context limit 1,000,000 tokens Output limit 65,536 tokens Tools Listed by endpoint Reasoning Listed by endpoint Promotional discount None reported Uptime · last 30 minutes 99.62% | Input $0.065 | Output $0.260 | Precision undeclared | Uptime (1d) 99.82% | ### Independent scores | LMArena Elo | 1397 default | | --- | --- | LMArena Elo under CC BY 4.0. Absence of another board is not a score of zero. ### Capability | Context window | 1M | | --- | --- | | Max output | 65K | | Input modes | text, image, video | | Tool use | yes | | Reasoning | optional | | Open weights | Unknown | ### Provenance | Price source | [openrouter.ai](https://openrouter.ai/api/v1/models) | | --- | --- | | Fetched | 2026-10-06 | | Quality data | verified | The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the... ## Questions this page answers What does Qwen3.5-Flash cost? $0.065/M in, $0.260/M out in this catalogue, as of the fetch date on this page. That is the API row, not a subscription. Does Qwen3.5-Flash have an independent quality score? Qwen3.5-Flash has an LMArena score in this catalogue. What beats Qwen3.5-Flash? DeepSeek V4 Flash 0423 has an equal-or-higher measured score and an equal-or-lower price, with capability trade-offs. Does this page use Artificial Analysis scores for Qwen3.5-Flash? No. Artificial Analysis figures are not published here. Quality on this page is LMArena Elo where a score exists; otherwise the row is unrated. MODEL MONUMENT ## Save or share this proof Download proof card · 1200 × 630 Preview and more sharing options Qwen: Qwen3.5-Flash. Balanced workload. Alternative has a trade-off. Evidence as of 06 Oct 2026. Copy model link Download square card · 1080 × 1080 Copy landscape image Share landscape card ## Related - Higher score and cheaper, with a named trade [DeepSeek V4 Flash 0423](/models/deepseek__deepseek-v4-flash/) - Nearby on the capability axis [Grok 4.7](/models/x-ai__grok-4.7/) - Same vendor [Qwen3.5-35B-A3B](/models/qwen__qwen3.5-35b-a3b/) - Qwen models [Qwen](/providers/qwen/) - Where this model appears [wire](/wire/) - Nearby on the capability axis [Grok 4.3](/models/x-ai__grok-4.3/) - Same vendor [Qwen3 VL 235B A22B Thinking](/models/qwen__qwen3-vl-235b-a22b-thinking/) - Where this model appears [significance](/significance/) - Nearby on the capability axis [Claude Haiku 4.5](/models/anthropic__claude-haiku-4.5/) - Same vendor [Qwen3.5-27B](/models/qwen__qwen3.5-27b/) - Where this model appears [cheapest-at](/cheapest-at/) ## Badge The verdict as one SVG, for a README or a docs page. It states this model's dominance status at the balanced workload on the LMArena lens, with the date it was computed, and it is rebuilt with the catalogue — so it changes when the verdict changes, including to one you would rather it did not. Markdown Copy [![Qwen3.5-Flash — Undominated.ai dominance verdict](https://undominated.ai/badge/qwen__qwen3.5-flash-02-23.svg)](https://undominated.ai/models/qwen__qwen3.5-flash-02-23/) HTML Copy Qwen3.5-Flash — Undominated.ai dominance verdict Direct file: [https://undominated.ai/badge/qwen__qwen3.5-flash-02-23.svg](https://undominated.ai/badge/qwen__qwen3.5-flash-02-23.svg) — a static SVG, written by scripts/build-badges.mjs on every build, so the copy you embed is never older than the last deploy. ## Continue your investigation - [Explore model families](/families/) - [Compare a shortlist](/compare/) - [Check a model](/check/) - [Understand the evidence](/methodology/)