What does Qwen3.8 Flash Next cost on RunInfra?

Input costs $0.12 per 1M input tokens. Cached input costs $0.01 per 1M cached input tokens. Output costs $0.40 per 1M output tokens.

What are the limits for Qwen3.8 Flash Next?

Context window: 262,144 tokens. Maximum request size: 3.5 MB per request. Maximum generated output: 262,144 tokens.

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Built for agents that replay context. Agent traffic resends the whole conversation on every tool call. Here the repeated part hits cache and bills at the cached input rate.

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Model Library

Built for agents that replay context. Agent traffic resends the whole conversation on every tool call. Here the repeated part hits cache and bills at the cached input rate.

RunInfraby RightNow

Join the community System status

Optimization agent Model APIs Pricing Startups Benchmarks Docs Research News Contact

Backed by

Combinator

AICPA Type II

SOC 2

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Part of RightNow

Security DPA AUP Cookies Terms Privacy

RunInfraby RightNow

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Qwen3.8 Flash Next | Model APIs | RunInfra

Model Library
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Qwen
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Qwen3.8 Flash Next

Qwen3.8 Flash Next

Qwen/Qwen3.8-Flash-Next-FP8

Get API key Chat Completions API reference

Qwen3.8 Flash Next is an LLM listed in RunInfra Model APIs. RunInfra serves it as Qwen/Qwen3.8-Flash-Next-FP8 at $0.12 per 1M input tokens and $0.40 per 1M output tokens. Its context window is 262,144 tokens. The API provides OpenAI-compatible chat completions and Anthropic-compatible Messages, POST /v1/messages.

Pricing

USD, pay per token

per 1M input tokens: $0.12
per 1M cached input tokens: $0.01
per 1M output tokens: $0.40

Access

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Provider: Qwen
API compatibility: OpenAI-compatible chat completions
Anthropic compatibility: Anthropic-compatible Messages, POST /v1/messages
Accepted input: Text only
Availability: Available
Data retention: Your prompts are never stored and never used for training.

Capacity

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Context window: 262,144 tokens
Maximum request size: 3.5 MB per request
Maximum generated output: 262,144 tokens

Capabilities

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Tool calling: Supported
JSON mode: Supported
Streaming: Supported
Precision: FP8, vendor-released checkpoint

View Full Spec

Gateway compatibility: OpenAI- and Anthropic-compatible APIs for compatible clients, tools, and gateways
Prefix caching: Automatic prefix caching runs on every replica, and requests from the same session or conversation are routed back to the replica that holds their cached prefix. A stable session hint or prompt_cache_key provides explicit grouping; otherwise RunInfra derives it from the start of the conversation. Hits remain best effort until eviction or a serve restart, never guaranteed. Cached input is billed at the cached input rate. Responses report cached token counts.
Cache retention: Prefix cache is held on the serving GPU and evicted under memory pressure. Retention is best effort.
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