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Qwen3 235B A22B FP8

Up to 30%

Qwen3 235B A22B FP8 is available on LLM.API as an OpenAI-compatible chat endpoint—route Alibaba quality through one key with transparent token pricing.

Start Using API

What is Qwen3 235B A22B FP8?

Qwen3 235B A22B FP8 is an Alibaba chat model exposed on LLM.API under id `qwen3-235b-a22b-fp8`. qwen3-235b-a22b-fp8 provided by novita. It is wired for API access through LLM.API with OpenAI-compatible patterns. Teams use it when they need reliable text generation with text inputs and text outputs over an OpenAI-compatible API.

Providers

LLM.API routes Qwen3 235B A22B FP8 to the providers below, with discounted effective rates versus list price.

List price by provider ($ / 1M tokens)

InputOutput
novita$0.2 in
$0.8 out

Provider list prices; the LLM.API discount applies on top.

ProviderPricingContextCapabilities
novita30% offin $200; out $800 per 1M tokens41K tokenstools, streaming, JSON

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.

Try this model

Test Qwen3 235B A22B FP8 right here — free to start.

Qwen3 235B A22B FP8
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Qwen3 235B A22B FP8 through the OpenAI-compatible API — POST /v1/chat/completions.

python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAP_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="qwen3-235b-a22b-fp8",
    messages=[
        {"role": "system", "content": "You are a precise product assistant."},
        {"role": "user", "content": "Give me three crisp launch checklist items."},
    ],
)
print(resp.choices[0].message.content)
{
  "model": "qwen3-235b-a22b-fp8",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Conversational UX

    Maintains coherent multi-turn assistant behavior for product chat surfaces. Grounded in the model's chat role rather than generic chat claims.

  • Analytical writing

    Produces clear analyses, comparisons, and decision memos from messy source material. Relevant for `qwen3-235b-a22b-fp8` workloads on LLM.API.

  • Multi-step reasoning

    Breaks down complex problems into intermediate steps before answering. Relevant for `qwen3-235b-a22b-fp8` workloads on LLM.API.

  • Structured outputs

    Can produce JSON-friendly or schema-oriented responses when prompted carefully. Grounded in the model's chat role rather than generic chat claims.

  • Tool-ready dialogue

    Works well in agent loops that call functions, browsers, or retrieval APIs. Tuned to how teams typically call Qwen3 235B A22B FP8.

6 Most Valuable Use Cases

  • Internal knowledge assistants grounded with your retrieval layer with Qwen3 235B A22B FP8
  • Policy Q&A bots with careful refusal behavior
  • Product analytics narration and anomaly explanations with Qwen3 235B A22B FP8
  • Coding agents for refactors, tests, and PR explanations
  • Multilingual localization drafts for UX copy with Qwen3 235B A22B FP8
  • Sales and success email drafting with CRM context

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.

    More performance, less spend.

  • Resilient Fallback Flows

    Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.

    Never go dark on users.

  • Deep LLM Observability

    Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.

    See every token, everywhere.

  • Task-Level Orchestration

    Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.

    Think tasks, not models.

  • High-Throughput Batch APIs

    Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.

    Scale from 1 to millions.

Why run Qwen3 235B A22B FP8 on LLM.API?

  • Unified AI Routing

    Practical: Reach Qwen3 235B A22B FP8 and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Compare provider price points and keep spend visible as you scale Qwen3 235B A22B FP8.

  • Reliability Layer

    Practical: Retry and route across configured providers when a single upstream blips.

  • Observability

    Practical: Trace prompts, tokens, and errors for Qwen3 235B A22B FP8 alongside the rest of your stack.

  • Drop-in SDKs

    Production: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

  • Model Breadth

    Production: Swap Qwen3 235B A22B FP8 for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • You want OpenAI-compatible chat completions through a single LLM.API key (Qwen3 235B A22B FP8)
  • You need a general-purpose text model for assistants, agents, or content workflows (Qwen3 235B A22B FP8)
  • Your prompts benefit from the model's family strengths (reasoning, speed, or cost) (Qwen3 235B A22B FP8)
  • You need provider failover options exposed for this model id (Qwen3 235B A22B FP8)

Avoid if...

  • You need pure embedding, OCR, or media generation instead of chat
  • You need guaranteed real-time hard latency SLAs without benchmarking the provider
  • Your use case depends on unpublished proprietary benchmarks not listed here
  • You require on-prem only deployment with no cloud inference

COMMUNITY

What developers say about Qwen models

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Qwen3 235B A22B FP8.

  • Qwen is widely described as the strongest open-weight coding family, with reviewers testing whether local Qwen can replace hosted frontier assistants for agentic coding.
  • Benchmarks published by developer blogs show production-usable code and solid architectural reasoning, especially in the Coder variants.
  • The honest verdict in most write-ups: excellent value and privacy, still behind the top proprietary models on the hardest long-horizon tasks.

SOURCES

Frequently Asked Questions

  • How do I call Qwen3 235B A22B FP8 via API?

    Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "qwen3-235b-a22b-fp8" and your LLM.API key. See the code snippet on this page.

  • How is Qwen3 235B A22B FP8 priced on LLM.API?

    Listed pricing metadata shows: In $0.2 / 1M tokens · Out $0.8 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • Which providers serve Qwen3 235B A22B FP8?

    LLM.API currently lists: novita. Availability can vary by region and account.

  • Does Qwen3 235B A22B FP8 support streaming?

    Yes—at least one listed provider advertises streaming.

  • What modalities does Qwen3 235B A22B FP8 support?

    Qwen3 235B A22B FP8 accepts text and produces text according to its architecture metadata on LLM.API.

  • Can I use tools or structured outputs with Qwen3 235B A22B FP8?

    Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.

  • When should I choose Qwen3 235B A22B FP8?

    Your prompts benefit from the model's family strengths (reasoning, speed, or cost) — especially when you specifically need Qwen3 235B A22B FP8.

  • Where is the canonical page for Qwen3 235B A22B FP8?

    https://llmapi.ai/models/alibaba-qwen3-235b-a22b-fp8/

  • What is Qwen3 235B A22B FP8?

    qwen3-235b-a22b-fp8 provided by novita. It is wired for API access through LLM.API with OpenAI-compatible patterns. On LLM.API it is addressed as `qwen3-235b-a22b-fp8`.

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