Qwen3.8-Flash
qwen3.8-flashQwen3.8-Flash by Qwen: 1M context, 128K max output, with Vision, Function Calling, Reasoning, Prompt Caching, Response Schema, Video, Streaming, Web Search. Via WandAPI, Input (prompt) costs 0.56 Credits / M tokens, 30% below list price. 7-day uptime 95.6%. Compatible with Anthropic Messages: swap the base URL and you are connected.
Capabilities
Listed exactly as the catalog flags them, including what this model does not support.
Vision
Natively multimodal: captioning, classification, visual Q&A, chart and screenshot understanding. Images are converted to tokens at the input rate.
Function Calling
Connect the model to external tools and APIs: it decides when to call which function and with what arguments, your code runs it. Force or forbid calls with tool_choice.
Reasoning
The model thinks before answering, which markedly improves multi-step planning and reasoning for coding, math and data analysis. Thinking tokens bill at the output rate.
Prompt Caching
Repeated prefixes (system prompts, long documents) hit the cache: reads cost far less than input, writes are priced by retention time.
Response Schema
Constrain output to a JSON Schema you provide for predictable, type-safe results without parsing free text.
Video
Video input understanding or video generation.
Streaming
Tokens arrive over SSE as they are generated; the first frame is forwarded immediately with no buffering. Claude Code, Codex and similar tools depend on this.
Web Search
Vendor-hosted live web retrieval; the model decides when to search and cites sources.
AudioNot supported
Audio input or speech output.
File InputNot supported
Upload PDFs and other documents directly; the model reads the whole document with native vision.
RealtimeNot supported
Bidirectional low-latency voice / text sessions over WebSocket.
SessionNot supported
Server-side multi-turn context (e.g. previous_response_id in Responses) so you need not resend history.
MediaNot supported
Image / video / music generation endpoints.
Multipart FormNot supported
multipart/form-data file-upload requests.
Binary ResponseNot supported
Endpoints that return raw audio / image bytes.
Reliability & performance
WandAPI probes this model through the real supply chain on a schedule — measured, not self-reported.
Latency & throughput
Protocols & code samples
Change the base URL to WandAPI, keep everything else. Native protocols pass straight through; “adapted” ones are translated by the gateway.
Anthropic SDK or any Messages-protocol client: point base_url at https://api.wandapi.com and use a WandAPI key.
curl https://api.wandapi.com/v1/messages \
-H "x-api-key: $WANDAPI_KEY" \
-H "anthropic-version: 2023-06-01" \
-H "content-type: application/json" \
-d '{
"model": "qwen3.8-flash",
"max_tokens": 1024,
"messages": [{"role": "user", "content": "Explain prompt caching in one sentence"}]
}'Full price list
List price → WandAPI price per channel, every pricing dimension, nothing hidden.
| Item | Unit | Qwen list price | Qwen (Special Pricing) ×0.730% off |
|---|---|---|---|
| Input (prompt) | per 1M tokens | 0.56 Credits | |
| Output (completion) | per 1M tokens | 1.89 Credits | |
| Cache read | per 1M tokens | 0.07 Credits | |
| Cache write (general) | per 1M tokens | 0.98 Credits |
“Off” is computed at 1 Credit = ¥1 and today’s rate: 1 − channel multiplier × (1 Credit in the list currency).
FAQ
How much does the Qwen3.8-Flash API cost?
Via WandAPI, Input (prompt) costs 0.56 Credits / M tokens, with 1 Credit = ¥1. That is 30% below the Qwen list price.
What are the context window and output limit of Qwen3.8-Flash?
Context window 1M tokens, up to 128K tokens per response.
Does Qwen3.8-Flash support function calling and structured outputs?
Function calling with tool_choice control is supported; structured outputs (JSON Schema) are supported.
How do I use Qwen3.8-Flash in Claude Code?
Set ANTHROPIC_BASE_URL=https://api.wandapi.com, ANTHROPIC_API_KEY to your WandAPI key and ANTHROPIC_MODEL=qwen3.8-flash, then run claude. No config files to edit.
How is the 95.6% uptime measured?
WandAPI sends probe requests to this model through the real supply chain on a schedule and divides successful probes by total probes over the last 7 days. When one channel fails the gateway fails over to a backup, so the figure reflects what end users actually see.
One API key for Qwen3.8-Flash and 30+ models
Free credits on sign-up, pay as you go, no monthly fee.