GPT API Free
One OpenAI- and Claude-compatible API key fronting GPT, Claude, Gemini, DeepSeek, Qwen, GLM, Kimi and MiniMax models.
Worth a look if you want one key, official OpenAI and Claude SDK compatibility, and named access to the GPT, Claude, Gemini, DeepSeek, Qwen, GLM, Kimi and MiniMax families without spending anything up front. The console gives you per-key model groups and usage limits plus per-request usage records and trend analysis, which is more management surface than a bare proxy. It is a poor fit for anything customer-facing, because the free quota pairs a 7-day points allowance with a 24-hour shared request pool and no published performance commitment. If your real problem is unpredictable per-request cost rather than model breadth, Tokenless (YC S26) is aimed at exactly that.
Verified 2d ago · liveness 67/100 · cite: rightaichoice.com/tools/gpt-api-free
- Developers comparing several model families from one integration
- Students and hobbyists working with no budget
- Researchers running side-by-side model evaluations
- Teams checking OpenAI-SDK compatibility before committing to a paid provider
- Customer-facing applications that need a contractual uptime commitment
- Workloads that need a reserved, non-shared request budget
- Teams whose CI depends on steady throughput under a shared 24-hour request allowance
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Skip GPT API Free if your workload needs a reserved, non-shared request budget or a published uptime commitment — its free quota pairs a 7-day points allowance with a 24-hour shared request pool.
The free tier is capped by a 24-hour shared request allowance as well as a 7-day points allowance, so your throughput can drop when other free users are busy even if your own points are untouched.
The free tier (GitHub-authorised key, 7-day points allowance plus a 24-hour shared request allowance) is built for individuals and classrooms with zero budget. Top-ups are sold as prepaid balance at "as low as 1–2 折 of official" list price, with no per-model rate card published, so it costs less than paying each provider at list but gives you no fixed rate to budget against — the opposite trade to Tokenless (YC S26), which routes each request to the cheapest suitable model.
In short
GPT API Free — One OpenAI- and Claude-compatible API key fronting GPT, Claude, Gemini, DeepSeek, Qwen, GLM, Kimi and MiniMax models. Best for Developers comparing several model families from one integration, Students and hobbyists working with no budget, Researchers running side-by-side model evaluations. Free to use.
What people actually say about GPT API Free — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
48 mentions across 4 sources (YouTube, Bluesky, GitHub, Lemmy) · researched Jul 18, 2026.
Average across the 4 sources that answered — each source counts once, not each post.
- +Free access to multiple top LLMs including GPT-4 and Claude.
- +Compatible with OpenAI libraries, making integration straightforward.
- +No credit card required to get started initially.
- +Active GitHub community with nearly 39k stars and frequent updates.
- +Supports chat completions and embeddings out of the box.
- −Free keys often show 'insufficient balance' or require payment to use.
- −Frequent API key authentication errors reported on GitHub.
- −Paid users report keys not working with no effective support.
- −Rate limits and availability constraints not clearly documented.
- −Some users label the service a scam due to hidden payment demands.
- • Deposit or payment method required to actually use API beyond initial test calls
- • Potential charges if using paid key features after free tier limits hit
Viability Score
How well maintained and how widely used is GPT API Free? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Free API key quota claimed by registering and authorising with GitHub
- OpenAI-compatible /v1/chat/completions endpoint
- Claude Messages API compatibility
- Responses API support
- Works with the official OpenAI SDK
- Works with the official Claude SDK
- Compatible with coding tools including Codex and Claude Code
- Named model access: OpenAI GPT series (example model string "gpt-5.2")
- Named model access: Anthropic Claude series
- Named model access: Google Gemini series
- Named model access: DeepSeek series
- Named model access: Alibaba Qwen series
- Named model access: Zhipu GLM series
- Named model access: Moonshot Kimi series
- Named model access: MiniMax series
About GPT API Free
GPT API Free, run at api.chatanywhere.tech, gives you a single endpoint and a single API key that front a list of model families from several vendors. The homepage names OpenAI's GPT series, Anthropic's Claude series, Google's Gemini series, DeepSeek, Alibaba's Qwen series, Zhipu's GLM series, Moonshot's Kimi series and MiniMax, with more vendors said to be added over time. You claim a free key quota by registering and authorising with GitHub. The free plan is governed by two limits at once: a 7-day points allowance and a 24-hour shared request allowance, and the site states that all currently open compatible endpoints are callable under that quota. Migration is the point. You call the service with the official OpenAI or Claude SDKs, and the homepage's own example posts to https://api.chatanywhere.tech/v1/chat/completions with a "gpt-5.2" model string. The documented API surfaces are Chat Completions, Responses and Claude Messages, and the site says Codex and Claude Code work too. Swapping an existing project over is mostly a Host and API key change: the site recommends api.chatanywhere.tech for callers inside mainland China and api.chatanywhere.org for overseas. The console steps are: create a key under ApiKey management, set a model group and usage limit on it, configure the Host and key in your SDK or tool, then check per-request usage and trends in the usage analysis view. Beyond the free quota, prepaid top-ups are advertised at "as low as 1–2 折 of official" and the balance is described as valid long-term. That pricing is quoted as a discount multiple of official list price rather than a fixed per-request rate. The audience is developers, students and researchers who want to compare several model families behind one integration without opening an account per vendor. It is not aimed at customer-facing workloads: throughput depends partly on other free users through the shared 24-hour request pool, and the homepage publishes no rate figure, latency target or uptime commitment. If your problem is unpredictable per-request spend rather than model breadth, Tokenless (YC S26), which automatically routes each request to the cheapest suitable model, takes the opposite approach.
Behind the Verdict
The pitch here is breadth on a zero budget. One endpoint, one key, and the homepage's example call names a "gpt-5.2" model string, so you can point an existing OpenAI SDK client at the Host, change the key, and be comparing GPT, Claude, Gemini, DeepSeek, Qwen, GLM, Kimi and MiniMax replies on the same prompt without signing up anywhere else. The documented surfaces are Chat Completions, Responses and Claude Messages, and the site says Codex and Claude Code work against it as well. If your agent harness already speaks one of those SDKs, the integration cost is a base URL and a key. What you get beyond the raw endpoint is modest but real: the user console lets you create keys under ApiKey management, assign a model group and a usage limit per key, and inspect usage detail and usage analysis for request trends, spend and model distribution. That is the difference between this and a plain reverse proxy — you can hand a limited key to a class or a teammate rather than sharing one unrestricted token. The honest constraint is the free quota's shape. It is governed by a 7-day points allowance and a 24-hour shared request allowance simultaneously, so your throughput is partly a function of traffic from other free users. The homepage publishes no rate figure, no latency target and no uptime commitment, which means there is nothing to plan capacity against. Model availability sits with the upstream vendors, who can move or retire a model string without notice, so a pinned model in a running deployment can stop working. And pricing above the free tier is quoted as a relative discount — "as low as 1–2 折 of official" — not a per-request dollar rate, which is awkward if you have to report forward spend in dollars. Where it fits: evaluation, prototyping, teaching, hackathons, and compatibility checks before you commit to a paid provider. Tokenless (YC S26) is the cleaner choice when the actual problem is cost control, since it picks the cheapest suitable model per request instead of leaving that decision to you; that is a different product with a different job, not a strict upgrade.
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Real-world workflow fit
Concrete scenarios for the personas GPT API Free actually fits — and what changes day-one when you adopt it.
You keep your existing OpenAI SDK client and change only the Host to api.chatanywhere.tech and the key you created in the console, then run the same prompt with different model strings across the GPT, Claude and Gemini families.
Outcome: You get a comparable output set from several model families without opening a separate account or payment method per vendor.
You authorise with GitHub for a free quota, create separate keys under ApiKey management with a model group and usage limit on each, and hand one to each participant.
Outcome: Students call compatible endpoints through one shared endpoint while you review per-request usage and model distribution in usage analysis.
You point a Codex or Claude Code session, or your own harness, at the gateway and re-run your retry, timeout and error-handling paths against a non-OpenAI model string.
Outcome: You find out whether your integration survives a base-URL and key swap before paying a provider to answer that question.
Use Cases
- Point an existing OpenAI SDK client at the gateway and compare GPT, Claude and Gemini replies on the same prompt
- Run a Claude Code or Codex workflow through one key while you evaluate which underlying model suits the task
- Stand up a multi-model chatbot prototype for a hackathon at zero cost
- Let a class or study group try several model families through one shared endpoint
- Verify that your retry, timeout and error-handling code survives swapping model vendors
- Check how a prompt behaves across Qwen, GLM, Kimi and MiniMax without opening four accounts
- Issue a separately limited key per teammate or student and review their spend in usage analysis
Models Under the Hood
as of 2026-09-01
Limitations
- The free quota runs on two limits at once: a 7-day points allowance and a 24-hour shared request allowance.
- The shared pool is the practical constraint — your throughput depends on traffic from other free users, not only your own.
- The homepage publishes no rate figure, latency target or uptime commitment, so there is nothing to plan capacity against.
- Model availability sits with the upstream vendors, who can deprecate a model string without notice; a pinned model in a running deployment can therefore stop working.
- Pricing above the free tier is quoted in relative terms (a discount multiple of official list price, "as low as 1–2 折") rather than a fixed per-request rate, which makes forward budgeting awkward for teams that report in dollars.
as of 2026-10-16
Verification history
We have re-verified GPT API Free 8 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 8 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published GPT API Free tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Individual developers, students and researchers who want one key to compare several model families without entering payment details.
What this tier adds
Starting tier: GitHub-authorised key quota, all currently open compatible endpoints callable, governed by a 7-day points allowance plus a 24-hour shared request allowance.
Paid top-up
Custom
Ideal for
Developers who have outgrown the free quota and want a long-lived prepaid balance rather than a monthly subscription per vendor.
What this tier adds
Adds prepaid balance on top of the free quota, advertised at "as low as 1–2 折 of official" list price with the balance valid long-term; same compatible endpoints as the free tier.
Where the pricing makes sense
The company stage and team size where GPT API Free's pricing actually pencils out — and where peers do it cheaper.
The free tier (GitHub-authorised key, 7-day points allowance plus a 24-hour shared request allowance) is built for individuals and classrooms with zero budget. Top-ups are sold as prepaid balance at "as low as 1–2 折 of official" list price, with no per-model rate card published, so it costs less than paying each provider at list but gives you no fixed rate to budget against — the opposite trade to Tokenless (YC S26), which routes each request to the cheapest suitable model.
Setup time & first value
How long it actually takes to get something useful out of GPT API Free — broken out by persona, not the marketing-page minute.
For a developer with an existing OpenAI SDK project: minutes, because the documented path is a new base URL (api.chatanywhere.tech in mainland China, api.chatanywhere.org overseas) plus a key created in the console. First-time users add the GitHub authorisation step to claim the free quota, then set a model group and usage limit on the key. Allow a first session for the classroom case, where you
Switching to or from GPT API Free
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From direct OpenAI API: change the base URL to the gateway Host and swap in your key; the homepage example calls /v1/chat/completions with a "gpt-5.2" model string.
- →From direct Anthropic API: the service documents Claude Messages compatibility, so move your Messages calls to the gateway Host and key.
- →From a Codex or Claude Code setup: configure the gateway Host and API key in those tools rather than rewriting your workflow.
- ↗To direct OpenAI API: keep the same OpenAI SDK call shape and point the base URL back at OpenAI with their key.
- ↗To direct Anthropic API: move your Messages calls back to Anthropic's endpoint.
- ↗To Tokenless (YC S26): move to per-request automatic routing to the cheapest suitable model if your priority shifts from model breadth to predictable spend.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “GPT API Free”, and we withheld 6: 6 did not mention GPT API Free. We are showing none, because we could not prove any of them are about GPT API Free.
Official links
Tools that pair well with GPT API Free
Common stack mates teams adopt alongside GPT API Free, with the specific reason each pairing earns its keep.
APIMart
APIMart is a discounted AI API gateway: one OpenAI-compatible endpoint for 190+ text, image, video, and audio models, billed pay-as-you-go
Inference Engine by GMI Cloud
GMI Cloud Inference Engine runs text, image, video, and audio models behind one OpenAI-compatible API on dedicated NVIDIA GPUs.
GPTProto
GPTProto is a unified AI API that routes 200+ text, image, and video models through one OpenAI-compatible key at 10–30% below official
Featured Head-to-Head Comparisons
Gpt Api Free vs Spider Cloud
If you need production-grade web data for AI agents or RAG, Spider Cloud wins with a dedicated crawling engine, 99.9% success rate, and advanced anti-detection — at $0.03/1K pages it's cost-effective for scale. If you're a student or hobbyist testing LLMs for free, GPT API Free is unbeatable for zero-cost access to multiple models, but cannot be used for high-reliability or large-scale applications.
Gpt Api Free vs Voyage Ai
For production RAG on sensitive enterprise data, Voyage AI's domain-specialized embeddings and compliance (SOC 2, HIPAA) are unmatched. GPT API Free is perfect for low-cost experimentation across multiple LLMs but lacks reliability and security for anything beyond prototypes. Choose based on your appetite for risk and scale.
Gpt Api Free vs Temporal Ai
These tools are complementary, not competitors. Temporal is for orchestrating durable, reliable AI agent workflows (crashes, retries, human-in-the-loop) – it's infrastructure. GPT API Free is for cheaply accessing multiple LLMs for testing. If you need a production-grade microservice orchestrator with built-in fault tolerance, choose Temporal. If you need free LLM API keys for prototyping, choose GPT API Free. Many teams will use both together.
Alternatives to GPT API Free
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APIMart
APIMart is a discounted AI API gateway: one OpenAI-compatible endpoint for 190+ text, image, video, and audio models, billed pay-as-you-go
Inference Engine by GMI Cloud
GMI Cloud Inference Engine runs text, image, video, and audio models behind one OpenAI-compatible API on dedicated NVIDIA GPUs.
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