Current status: October 1, 2026
This comparison covers the current DeepSeek API models and the January 2026 Qwen3-Max-Thinking release. It compares deployment choices and published prices; it does not claim a new head-to-head benchmark result.
When should I choose DeepSeek over Qwen3 Max Thinking?
Start with DeepSeek V4.1 Flash when token cost, 1M context or image input matters. Evaluate Qwen3-Max-Thinking when your application uses Alibaba Cloud Model Studio and its supported reasoning tools. Compare task success and total spend in your own workflow before choosing.
Which Qwen3 Max price applies to thinking mode?
For Singapore International deployment, Alibaba Cloud lists input/output prices of $1.20/$6 up to 32K input tokens, $2.40/$12 above 32K and up to 128K, and $3/$15 above 128K and up to 256K, per million tokens. The cheaper Frankfurt Global tier is listed for non-thinking mode only.
Can I self-host both models?
DeepSeek publishes V4 Pro and V4.1 Flash weights under the MIT license. The Qwen3-Max-Thinking sources checked here document Qwen Chat and Alibaba Cloud Model Studio access; they do not establish a downloadable checkpoint or a self-hosting license for this model.
DeepSeek's current names are deepseek-flash for V4.1 Flash and deepseek-v4-pro for V4-Pro-0813. Qwen's thinking snapshot is qwen3-max-2026-01-23. Use the explicit snapshot when checking regional capabilities in Model Studio.
For a broader provider comparison, see the task-by-task model guide. For DeepSeek migration details, use the DeepSeek V4 guide.
Pricing, model limits and use cases, reviewed October 1, 2026
DeepSeek V4.1 Flash has lower listed token rates than Qwen3-Max-Thinking on Singapore International deployment and a larger context window. Qwen is worth evaluating when you already use Model Studio or need its documented search and code-interpreter workflow. Region, thinking mode and request size affect the comparison.
- DeepSeek V4.1 Flash replaced the original V4 Flash API model on September 10
- DeepSeek lists 1M context and up to 384K output for Flash and Pro
- Qwen announced Qwen3-Max-Thinking on January 25, 2026
- Qwen's thinking snapshot has 262,144 context and a 32,768-token maximum answer output
- Qwen prices and tool support depend on deployment region and mode
Choose between these models by testing the work your application performs. DeepSeek offers open weights and lower listed token costs for the deployment compared here. Qwen offers hosted reasoning through Model Studio, with tools that vary by region.
Short answer
Pick a first test for your application's workload.
Where to start
| Workload | First model to evaluate | Reason |
|---|---|---|
| Bulk coding or long document requests | DeepSeek V4.1 Flash | Lower listed token rates and 1M context |
| Self-hosted reasoning | DeepSeek V4 Pro or V4.1 Flash | Published weights with MIT license terms |
| Reasoning with Model Studio tools | Qwen3-Max-Thinking | Documented hosted search and code interpreter; check regional support |
| Existing DeepSeek application | Current Flash and Pro | Test both on your own tasks before changing the route |
Model names and access
The API name determines which release you test.
Published limits and availability
| Item | DeepSeek | Qwen3-Max-Thinking |
|---|---|---|
| Current API models | deepseek-flash; deepseek-v4-pro | qwen3-max-2026-01-23; qwen3-max alias |
| Context | 1M for both models | 262,144 tokens |
| Maximum answer output | 384K for both models | 32,768 tokens in thinking mode |
| Image input | Flash supports vision; Pro does not | Text input in the Model Studio specification |
| Tool access | Tool calls and Responses API | Function calls in Singapore International and Frankfurt EU; web search in Singapore |
| Self-hosting | MIT-licensed weights | Checked sources document hosted access |
Source: DeepSeek pricing and changelog; Alibaba Cloud qwen3-max model documentation
Qwen's January announcement describes adaptive search, memory and code interpreter in Qwen Chat. Model Studio documents search, web extraction and code interpreter for the thinking snapshot. Its regional capability tables differ: Singapore International supports function calling and web search, while Frankfurt EU lists function calling without web search. Confirm the endpoint and mode your application will use.
Keep API versions separate
The retired deepseek-v4-flash API name temporarily routes to V4.1 Flash. Results for the original V4 Flash do not describe the replacement model. Qwen3-Max-Thinking is the named January release in this comparison; it is not presented here as Qwen's latest model.
API pricing
Compare the same deployment mode and include reasoning output.
Listed prices checked October 1, 2026
| Model / deployment | Uncached input | Output | Condition |
|---|---|---|---|
| DeepSeek V4.1 Flash | $0.30 / $0.15 | $1.20 / $0.60 | Peak / off-peak |
| DeepSeek V4 Pro | $1.32 / $0.66 | $3.96 / $1.98 | Peak / off-peak |
| Qwen3-Max-Thinking, Singapore International | $1.20 | $6 | Input up to 32K |
| Qwen3-Max-Thinking, Singapore International | $2.40 | $12 | Input above 32K and up to 128K |
| Qwen3-Max-Thinking, Singapore International | $3 | $15 | Input above 128K and up to 256K |
Source: https://api-docs.deepseek.com/quick_start/pricing/ ; https://www.alibabacloud.com/help/en/model-studio/model-pricing
All prices are USD per million tokens. DeepSeek peak hours are Monday–Friday, 01:00–04:00 and 06:00–10:00 UTC, excluding Chinese public holidays; other hours are off-peak. Flash cached input is $0.006/$0.003 and Pro cached input is $0.044/$0.022, peak/off-peak. Alibaba's output price covers chain-of-thought and answer tokens. The table uses Singapore International thinking-mode rates; cheaper Frankfurt Global non-thinking rates do not describe that configuration.
Lower token prices can reduce bulk-work costs, but retries, tool results and long reasoning responses also affect the bill. Measure total spend per accepted result when you compare these models.
Provider benchmark results
The providers report different tests and configurations.
Selected published results
| Model | Benchmark | Provider-reported result | Source context |
|---|---|---|---|
| DeepSeek V4.1 Flash | Terminal-Bench 2.1 | 90.6 | DeepSeek model card; DeepSeek Harness Minimal, max reasoning |
| Qwen3-Max-Thinking | LiveCodeBench v6 | 85.9 | Qwen's January 25 announcement |
| Qwen3-Max-Thinking | SWE Verified | 75.3 | Qwen's January 25 announcement |
| Qwen3-Max-Thinking | HLE with tools | 49.8 | Qwen's January 25 announcement |
Source: DeepSeek V4.1 Flash official model card; Qwen3-Max-Thinking official blog
Use these results to choose an evaluation
These figures come from the providers. Different benchmarks, release dates and agent setups prevent a direct winner from this table. Run a shared set of coding or reasoning tasks with the tools and token limits your application uses.
Which model should you choose?
Evaluate the trade-offs that affect your deployment.
For high-volume coding transformations, document extraction or image-assisted tasks, start with Flash and check accepted results, latency and cost. For a DeepSeek-only reasoning application, include Pro in the evaluation rather than assuming it wins every task. Both have published weights, although serving them requires a suitable inference deployment.
For an application built around Alibaba Cloud, test Qwen's thinking snapshot with your chosen region's supported tools. If the workflow depends on web search, the Frankfurt EU capability table changes the choice. If it requires a local checkpoint, the checked Qwen3-Max-Thinking sources do not supply the weight and license evidence needed for that deployment.
Official sources checked
Release, pricing and access sources reviewed October 1, 2026.
- DeepSeek API changelog
- DeepSeek models and pricing
- DeepSeek V4.1 Flash model card
- DeepSeek V4 Pro license
- Qwen3-Max-Thinking announcement
- Alibaba Cloud model limits and regional capabilities
- Alibaba Cloud Model Studio pricing
Before choosing
Check the full workload on the deployment you plan to use.
Record the model ID, region, thinking mode, input size and total token spend for each test. Compare successful task completions under the same constraints. Use the DeepSeek guide for migration steps and the cost calculator to estimate request volume.
Founder of Spectrum AI Labs — testing AI tools and models, and writing up what actually ships.
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