

Qwen3.7 Flash and Qwen3.7 Plus side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.
Qwen3.7 Flash and Qwen3.7 Plus are both Alibaba Cloud models in the Text Generation category, available through the EmpirioLabs API.
| Spec | Qwen3.7 Flash | Qwen3.7 Plus |
|---|---|---|
| Model ID | qwen3-7-flash | qwen3-7-plus |
| Author | Alibaba Cloud | Alibaba Cloud |
| Released | Jul 15, 2026 | Jun 1, 2026 |
| Context window | 983.6K tokens | 983.6K tokens |
| Max output | 65,536 tokens | 65,536 tokens |
| Input | Text Image Video | Text Image Video |
| Output | Text | Text |
| Structured output | JSON Schema | JSON Schema |
| Region | Singapore | Singapore |
| Endpoints | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/qwen3-7-flash:generateContent | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/qwen3-7-plus:generateContent |
| Capabilities |
Live rates from the EmpirioLabs catalog for both models. Each rate card always matches what the API charges.
Request parameters each model lists on EmpirioLabs, with the allowed values or range where one applies. A dash marks a parameter the model does not list.
| Parameter | Qwen3.7 Flash | Qwen3.7 Plus |
|---|---|---|
| temperature | 0 to 1.99 Default: 0.7 | 0 to 1.99 Default: 0.7 |
| top_p | 0 to 1 Default: 0.9 | 0 to 1 Default: 0.9 |
| max_tokens | 1 to 65536 | 1 to 131072 |
| stop | string | string |
| enable_thinking | boolean Default: true | boolean Default: true |
| reasoning_effort | none, low, medium, high, max | none, low, medium, high, max |
| thinking_budget | 1 to 131072 | 1 to 262144 |
| preserve_thinking | boolean Default: false | boolean Default: false |
| seed | 0 to 2147483647 | 0 to 2147483647 |
| top_k | 1 to 100 | 1 to 100 |
| presence_penalty | -2 to 2 | -2 to 2 |
| repetition_penalty | 0.1 to 2 | 0.1 to 2 |
| n | 1 to 4 Default: 1 | 1 to 4 Default: 1 |
| logprobs | boolean Default: false | boolean Default: false |
| top_logprobs | 0 to 5 Default: 0 | 0 to 5 Default: 0 |
| vl_high_resolution_images | boolean Default: true | boolean Default: true |
Token pricing is tiered by prompt size and steps up above 32K and again above 256K input tokens. Cached prompt tokens are billed at the implicit cache rate for the matching tier. Web Search, Text-to-Image Search, and Image-to-Image Search are billed only when invoked.
Text-to-Image Search and Image-to-Image Search use the Image Search pricing row. Thinking tokens are billed as output tokens.
Pricing is 3x for input/output above 256K tokens. Web Search, Text-to-Image Search, and Image-to-Image Search are billed only when invoked.
Text-to-Image Search and Image-to-Image Search use the Image Search pricing row. Thinking tokens are billed as output tokens.
Qwen3.7 Flash serves the OpenAI-compatible Chat Completions API. Point any OpenAI SDK at https://api.empiriolabs.ai/v1 with your EmpirioLabs API key and use the model id qwen3-7-flash. Both models are called through the same endpoint. Set model to qwen3-7-flash or qwen3-7-plus. Get an API key from the EmpirioLabs dashboard.
curl https://api.empiriolabs.ai/v1/chat/completions \
-H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-7-flash",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'Qwen3.7 Flash is the newer release (Jul 15, 2026); Qwen3.7 Plus was released on Jun 1, 2026. Both models have a context window of 983.6K tokens. Capabilities listed only for Qwen3.7 Flash: cache. The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.
Qwen3.7 Flash is the newer release (Jul 15, 2026); Qwen3.7 Plus was released on Jun 1, 2026.
Both models list the same rate for Web search (per call when invoked) and Text-to-image search (per call when invoked). Both live rate cards are on this page and always match what the API charges.
Yes. Both models use POST /v1/chat/completions with the same EmpirioLabs API key, so most integrations switch by changing the model value. Check the parameters table on this page first if you rely on a model-specific parameter.
Yes. Open each model in the EmpirioLabs playground and run the same prompt on both, with the parameters the API exposes.
Check out our pricing or reach out if you want your own model deployed on our stack.