DeepSeek vs Qwen

DeepSeek vs Qwen is a choice by job: start with Alibaba's Qwen3.8-Flash for inexpensive image, video and text requests, and evaluate DeepSeek-V4.1-Flash-1017 for coding agents and repeated-context work. Both families advertise 1M-token API contexts, but the Qwen vs DeepSeek decision changes when you compare downloadable weights, licenses and hosting.

Verified on 21 October 2026 against DeepSeek's live API documentation and model cards, Qwen's release material, and Alibaba Cloud Model Studio's model and pricing pages. These recommendations combine documented capabilities and calculated costs; they are not results from a hands-on model test.

DeepSeek vs Qwen: Which Should You Pick?

Pick Qwen3.8-Flash for a founder's general multimodal product. Multimodal means accepting more than text: here, images and video as well. It is the cheaper uncached Flash route in the compared US and International scopes. Start there for a support assistant that reads screenshots or a product that summarizes demonstration videos. Escalate difficult work to Qwen3.8-Max only when your evaluation shows that it earns the extra spend.

Pick DeepSeek-V4.1-Flash-1017 as the first coding-agent challenger to evaluate. An agent is a model connected to tools that can inspect files, execute commands and revise its work. DeepSeek's current Flash has strong lab-reported coding results, image input and unusually cheap cached input. It is a compelling candidate for a repository agent that repeatedly reads the same instructions and source material. That recommendation is an evaluation priority, not a claim that it wins every coding task.

Pick Qwen's US deployment scope when US-only managed inference is a requirement. Choose the scope explicitly; an endpoint in Virginia can also use a Global scope. For permissively licensed flagship weights under your own operation, DeepSeek has the simpler license. For a smaller self-hosted candidate, evaluate Qwen3.8-27B instead of trying to squeeze either giant flagship into a small server.

Keep DeepSeek-V4-Pro-0813 for text work that benefits from its own evaluation results. Pro does not accept images on the direct API. Paying for the Pro name does not upgrade Flash's vision workflow. The DeepSeek V4 guide explains that split in more detail.

These calls prioritize input type, deployment restrictions, task completion and total billed usage, in that order. A disallowed hosting route or missing input modality cannot be repaired by a better benchmark score.

Current Models at a Glance

DeepSeek's direct API maps deepseek-flash to DeepSeek-V4.1-Flash-1017 and deepseek-v4-pro to DeepSeek-V4-Pro-0813. Alibaba lists Qwen3.8-Max, its upgraded Qwen3.8-Max-0902 snapshot, and Qwen3.8-Flash. The generic names and the dated snapshots are not interchangeable evidence. DeepSeek model mapping, Qwen Max and snapshot documentation, Qwen Flash documentation.

Prices below are USD per million tokens, uncached input / output. DeepSeek prices are direct; Qwen prices are for Singapore International or Virginia US deployment scopes. Tokens are the pieces of text a model processes and bills.

Sources: DeepSeek limits and pricing, Alibaba pricing by region and scope, the model pages above, and the exact weight licenses and regional documentation linked below. This is a route-specific comparison: another host's price or context limit is a separate offer.

Coding and Agent Work: Start With DeepSeek Flash, Use Qwen for Visual Workflows

DeepSeek is the first candidate for a text-heavy coding agent; Qwen is the first candidate when the agent must work across video and visual interfaces. Both expose tool calling. The useful distinction is whether the surrounding application can supply the right evidence and reliably execute the model's next action.

What the Labs' Coding Scores Establish

DeepSeek reports 77.0 on DeepSWE v1.1 for Flash-1017 using Mini-SWE-V2, and 42.3 on Terminal-Bench 4.0 using Claude Code. Those are DeepSeek's own published measurements. They make Flash-1017 worth putting into a coding evaluation; they do not supply a universal accuracy percentage. Flash-1017 model card.

For the older Terminal Bench 2.1 benchmark, DeepSeek reports 87.9 for Pro-0813 using its own harness in minimal mode at maximum reasoning effort. Qwen reports 86.6 for the original Qwen3.8-Max using Claude Code. Qwen also reports 56.6 on DeepSWE 1.1, selecting its better result across two harnesses. These are each lab's own results under different setups. Subtracting them does not produce a controlled head-to-head advantage. Nor should the original Max scores be relabeled as measurements of Max-0902. DeepSeek Pro-0813 results, Qwen's published evaluation notes.

For a senior engineer, the decisive trial is a fixed set of your repository's issues with the same tests, tool permissions and stopping rules. Count accepted fixes, regressions, elapsed time and billed tokens, including failed attempts. A cheaper generation that needs repeated repair may be the more expensive completed task.

Qwen3.8-Max is the escalation candidate for a visual agent, such as one that inspects an application, changes its layout and checks the result. Qwen's release describes visual feedback during execution, while Model Studio lists image and video input for both Max and Flash. That supports a workflow recommendation, not an assertion that Qwen generates better interfaces on every brief. Qwen's multimodal agent design.

The production cost of switching is often in the harness, the software that manages tools and conversation history. Preserve the correct reasoning messages, handle tool errors, cap retries and keep destructive actions behind your application's permissions. An API-compatible request shape does not make two models behave identically.

Multimodal Input: Qwen Wins on Breadth, DeepSeek Flash Remains an Image Candidate

Choose Qwen for a product that must ingest both images and video through the named models. Both Qwen3.8-Max and Qwen3.8-Flash accept text, images and video and produce text. A founder building a support tool can use the same model family for a screenshot and a recorded reproduction of a bug. Max capabilities, Flash capabilities.

DeepSeek Flash can inspect images; treating the whole DeepSeek family as text-only is incorrect. Its documented preprocessing resizes large images to roughly the area of 1300 × 1300 pixels, with at most 1,024 tokens per image. For dense engineering drawings or tiny screenshot text, inspect whether that resizing loses evidence before choosing it for the workflow. DeepSeek vision processing.

Do not infer audio support from the Qwen name. Qwen3.8-Omni-Flash is a separate product in the current family. Its capabilities and billing need a separate evaluation; the ordinary Flash and Max text rates here are not an audio quote. Qwen's current releases.

Long Context: DeepSeek Wins the Output Ceiling, Qwen Wins the Video Use Case

Neither family wins simply by advertising a million-token context. Context is the working space available to the request, not a promise that every fact in a long input will be recovered correctly. Both hosted families advertise 1M; DeepSeek's larger documented output ceiling matters if your job requires a very long generated result. DeepSeek API limits.

Qwen's hosted Max and Flash pages distinguish the total context from maximum input, answer length and reasoning length. Their maximum input is 991,808 tokens, or 983,616 in thinking mode, and their listed maximum answer is 131,072 tokens. You cannot add every advertised maximum together and expect one valid request. Leave room for the answer and tool messages. Qwen Max context limits, Qwen Flash context limits.

For a CTO processing long video evidence alongside documents, Qwen's input support is the useful advantage. For a text generation system with unusually long outputs, DeepSeek is the stronger specification fit. For a repository assistant, evaluate retrieval and editing accuracy before loading every file into every request. More working space does not remove the need to select relevant material.

The self-hosting distinction is sharper: Qwen3.8-2.4T-A95B starts at 262,144 native context, extensible to 1,010,000, while its hosted Max product provides 1M by default. Downloading the weights is not the same deployment configuration. Official Qwen weight card.

API Cost: Qwen Wins Uncached Flash, DeepSeek Can Win Repeated Context

Qwen Flash is the lower-cost starting point until reuse and output length change the calculation. Cached input is a repeated prompt prefix the provider can reuse at a discounted rate. It is especially relevant to an agent that repeatedly sends the same instructions and repository context.

DeepSeek's current off-peak rule is precise: peak billing applies 01:00 to 04:00 and 06:00 to 10:00 UTC, Monday through Friday, excluding Chinese public holidays. Every other hour is off-peak, including weekends and Chinese public holidays in full. Off-peak rates are half the peak rates. This is not a generic overnight discount in your local time zone. DeepSeek's billing rule.

For cache hits, direct DeepSeek Flash charges $0.003 off-peak or $0.006 peak per million input tokens. Qwen3.8-Flash lists $0.016 for implicit-cache input in the International and US scopes. Qwen's general cache guide explicitly makes the current models exceptions to its generic discount, so use the model's listed price. DeepSeek cache pricing, Qwen Flash cache pricing, Qwen cache exceptions.

The Same Workload, With and Without Cache Hits

Take an illustrative workload totaling 20 million input tokens and 1 million billed output tokens, spread across requests. Assume the same token counts and cache-hit share on both providers; this isolates the rate difference rather than pretending their tokenizers or reasoning lengths are identical.

With no cache hits, the calculated bill is $3.60 for off-peak DeepSeek Flash, $7.20 at peak, and $3.47 for Qwen3.8-Flash in the compared scopes. With 80% of input tokens served from cache, it becomes $1.248 off-peak or $2.496 peak for DeepSeek, versus $1.326 for Qwen. These totals exclude tool charges, retries, taxes and explicit-cache creation or storage.

The crossover is 50% cache hits for this input-heavy example. Above that, DeepSeek off-peak becomes cheaper; below it, Qwen does. More generally, let h be the input cache-hit share and r the output/input token ratio. The DeepSeek-minus-Qwen bill per million total input tokens is -0.013h + 0.13r dollars, giving a break-even rule of h = 10r. If output is at least a tenth of input, DeepSeek cannot be strictly cheaper under these equal-cache assumptions. At peak, Qwen stays cheaper throughout this particular 20:1 example.

This is a small saving in the illustrated cached case. A task-quality advantage, a shorter reasoning trace or an extra retry can outweigh it. Use the crossover to decide what to measure, not to route production solely by the clock.

For the larger pair, DeepSeek Pro's uncached input and output rates are below Qwen Max's in the compared scopes. Qwen Max must earn its premium through the job it completes or the deployment route it supplies. Keep the full DeepSeek billing reference in the DeepSeek pricing guide.

Open Weights and Licenses: DeepSeek for the Flagship, Qwen for a Smaller Deployment

DeepSeek wins the flagship license comparison; Qwen wins the smaller-model starting point. Open weights means you can obtain the model files. It does not promise that the license is unrestricted, that your hardware can serve them, or that the hosted API's surrounding features come with the download.

The exact DeepSeek-V4.1-Flash-1017 and DeepSeek-V4-Pro-0813 repositories state that their code and weights use the MIT License. Flash's card also supplies a reference encoder instead of a Jinja-format chat template. Your deployment still needs correct prompt encoding, inference software and tool execution. Flash card and license, Pro card and license.

Qwen3.8-2.4T-A95B uses the custom Qwen3.8-Max License. It grants broad use, modification and deployment rights, but carries conditions a product founder should read before adopting the checkpoint. In particular:

• A commercial product or service exceeding 100 million monthly active users or US$20 million monthly revenue must prominently display the respective model name. Copyright and permission notices must also be preserved.
• A licensee or affiliate in the defined Model as a Service or AI Work Assistant business must obtain a separate Qwen license before commercial use if aggregate revenue exceeds US$50 million over any consecutive 12 months. The internal-use exception requires that the software, outputs and underlying capabilities are not made available to third parties.

Those categories have definitions and exclusions in the license; “we are an AI startup” is not enough to determine whether they apply. Review the exact business model against the official license text.

There is also a capability gap: the released flagship checkpoint is a text model. Its card explicitly lists vision input, non-thinking support and built-in tools among the hosted Max product's additional features. A prototype built on hosted Max's image input cannot migrate unchanged to those weights. Qwen's hosted-versus-weights distinction.

For a solo builder or small infrastructure team, Qwen3.8-27B is the more sensible first self-hosting candidate. It is a dense 27B vision-language model with image and video understanding, and its exact license is Apache 2.0. It is a different checkpoint, not a local replica of Max or the Flash API. Hardware needs still depend on precision, context and concurrency. Qwen3.8-27B card, its Apache license.

API Hosting: Qwen Wins When You Need a Defined US Scope

Choose an operator and inference scope before approving the model family. Model Studio separates the region, which determines the access point and storage, from the deployment scope, which determines where inference runs. Alibaba's regional architecture.

For Qwen, Virginia with US scope confines inference to the United States. Virginia with Global scope can use nodes in mainland China and overseas. Singapore with International scope uses inference nodes outside mainland China, while static data stays in the selected region. A Singapore endpoint does not mean all computation stays in Singapore. Virginia scope definitions, Singapore scope definitions.

That distinction also explains lower advertised Qwen prices. Global-scope rates include $1.65 / $4.951 for Max and $0.113 / $0.382 for Flash, per million input/output tokens. Those are not the US-only prices used above. Buying the lower rate can mean buying a different inference boundary. Alibaba's regional pricing.

DeepSeek's direct API uses api.deepseek.com. Its published privacy policy says covered Personal Data is collected, processed and stored in the People's Republic of China; the Open Platform terms reference that policy for developer personal information and set out downstream end-user responsibilities. This does not establish every inference server's location, and it does not describe a copy of the weights that you operate yourself. It also does not give you the explicit US-scope choice documented by Alibaba. DeepSeek API endpoint, privacy policy, Open Platform terms.

A mid-market CTO should approve the exact service, workspace scope, retention arrangement and use case. If a managed route fails that review, evaluate a separately hosted or self-operated checkpoint on its own terms. The DeepSeek workplace safety guide covers the broader service and data questions.

Qwen vs DeepSeek: Switching Costs and Who Should Stay Put

Switch when the new route fixes a named constraint or improves completed-task economics. Keep your current provider if it already meets the input, hosting and quality requirements and the apparent saving disappears after retries or integration work.

DeepSeek is a Qwen alternative for a repeated-context coding agent or a flagship self-hosting plan that needs MIT weights. Qwen is a DeepSeek alternative for a managed video workflow, a defined US inference scope, or a smaller downloadable vision-language checkpoint. If the shortlist has grown beyond these two families, use the Chinese AI models comparison to place them in the wider field.

The migration work has three parts. First, change the endpoint, credentials and exact model identifier together. Second, adapt reasoning controls, tool-message handling, image or video inputs and structured-output validation. Third, rebuild the operational assumptions: caches do not transfer between providers, region-bound credentials must match the selected service, and self-hosting adds capacity and deployment work.

Qwen's release documents reasoning_effort and preserved thinking; DeepSeek publishes its own thinking and encoding behavior. Reuse your task definitions and acceptance tests, but validate the conversation format for the destination. For new Model Studio deployments, Alibaba recommends workspace-specific endpoints. Qwen integration details, DeepSeek encoding details, Model Studio endpoint guidance.

Monday move: select a small set of representative jobs, including a failed job from your current system. Run both candidates with the same allowed tools and acceptance criteria. Record the exact checkpoint, region, scope, reasoning setting, cache-hit tokens, output tokens, completion result and total cost. Move one bounded workflow only after the winning route clears those checks.

Frequently Asked Questions

What's the best Qwen model?

Qwen3.8-Max is the current flagship, with Max-0902 documented as an upgraded snapshot. Qwen3.8-Flash is the better starting point when inexpensive hosted image, video and text processing matters. For a smaller self-hosted model, evaluate Qwen3.8-27B separately.

How accurate is DeepSeek?

There is no single accuracy rate across tasks. Its lab publishes benchmark-specific scores for Flash-1017 and Pro-0813; those do not predict your application's error rate. Measure accepted outputs and failures on your own representative workload.

Who does Qwen?

Qwen is Alibaba's model family. The hosted products are available through Qwen Cloud and Alibaba Cloud Model Studio, while particular checkpoints are also released as downloadable weights.

Is Qwen as good as DeepSeek?

For a hosted image-and-video product, Qwen has the broader documented input support. DeepSeek is a strong coding-agent candidate and offers simpler licensing for the current flagship weights. The job and deployment route determine the recommendation.

Why is Qwen free?

Some Qwen weights can be downloaded without a license fee under their stated terms. That does not make GPU operation or the hosted API free. Check the exact checkpoint's license; Qwen3.8-Max's weights and Qwen3.8-27B use different licenses.

Is Qwen allowed in the USA?

Alibaba documents Qwen model availability under a US deployment scope. Service availability is not a determination that a particular organization or use case is permitted to use it. Apply your organization's procurement and data requirements to the exact service and scope.

How expensive is Qwen?

In the International and US scopes compared here, Qwen3.8-Flash is $0.15 per million uncached input tokens and $0.47 per million output tokens; Max is $2 and $6 respectively. Global-scope and cache-hit prices differ. Use the scope-specific rates above.

Is Qwen actually good?

Its documented tool calling, image and video inputs, and lab-published coding evaluations justify a product evaluation. Start with Flash for the ordinary workload and promote jobs to Max only when better completion quality earns its additional cost.

Get the AI Tools Map for Business Owners to place this model decision inside your wider AI stack.