ChatFire Review: Pricing & Comparison

¥0.5-1/USD: how is this price even possible

ChatFire’s (api.chatfire.cn) pricing is one of the most striking numbers among domestic relays: a Claude/GPT exchange rate of ¥0.5-1 per dollar.

The official exchange rate is around ¥7.2/USD, and most legitimate relays getting down to ¥2-4/USD is already a big discount. So what does ChatFire’s ¥0.5-1 range actually imply?

It’s about as close to certain as it gets: pricing this low comes from unofficial channels for obtaining API access, commonly including:

• Reverse engineering (bypassing the API to access the model directly)
• Account pools (rotating through a batch of individual accounts)
• Purchasing expiring account credits or gift cards
• Exploiting regional or policy-based price differences

That doesn’t mean ChatFire is unusable. In practice, a fair number of developers in mainland China use low-price sites like this for daily tasks (code assistance, document generation, content creation) on an ongoing basis without running into problems.

But it does carry a few real implications:

1. Quality degradation risk: models accessed through unofficial channels may respond at lower quality than the official API, making them unreliable for tasks that need precise reasoning
2. Instability: account-pool-based services can be interrupted when accounts get suspended, and generally can’t guarantee an SLA
3. Regulatory risk: the legal standing of reverse-engineered access is unclear

A pragmatic perspective

For specific use cases, ChatFire’s ultra-low pricing has genuine value:

Tasks well suited to ChatFire:

• High-volume batch text processing (content summarization, keyword extraction, format conversion) — tolerant of quality variance
• Rapid prototyping — the functional testing phase doesn’t need top-tier quality
• Learning and experimentation — no production data involved, so quality fluctuations are manageable
• Price-sensitive, non-critical-path tasks

Scenarios where ChatFire isn’t a good fit:

• Production scenarios with strict output-quality requirements (contract review, medical consultation, financial analysis)
• User-facing AI interactions (chatbots, customer service systems) — users will directly notice a drop in quality
• Scenarios with data privacy requirements — the data flow through unofficial channels isn’t transparent

Model coverage

As a multi-function aggregation platform, ChatFire’s coverage is fairly broad:

Text models:

• The GPT lineup (GPT-5.5, GPT-4o)
• The Claude lineup (Sonnet 4.6, etc.)
• DeepSeek V4 Pro/Flash
• Domestic models: Doubao, Ernie, Qwen, and others

Image generation:

• Midjourney (via an unofficial interface)
• The Flux family
• DALL-E 3

Video generation:

• Some mainstream video generation models (check the official site for specifics)

How it compares to other low-price sites

There are other low-price relays in the domestic market, and ChatFire’s distinguishing traits are:

• Compared to platforms like gptgod that rely mainly on reverse engineering, ChatFire has broader model coverage
• Compared to low-price relays focused purely on Claude, ChatFire’s mix of domestic models is more complete
• Compared to AzAPI’s multimodal coverage, ChatFire is cheaper, but quality stability may be worse

The cheapest site isn’t necessarily the best choice, but it does have a clear use case of its own.

If what you need is “get an AI pipeline prototype running at the lowest possible cost,” ChatFire’s low pricing can help keep your early exploration costs down. Once your product moves into production, we’d recommend migrating to a more stable platform, such as SiliconFlow (domestic open-source) or MoleAPI’s direct connection to mainstream models.

Information verified 2026-07-04. The actual service quality behind the ultra-low exchange rate needs to be tested yourself — check api.chatfire.cn’s live pricing for the latest figures.

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