We're happy to announce that we've enlisted Fireworks AI as PayPerQ's primary provider for open-source models.

In AI inference, quality, latency, reliability, and privacy vary a lot — even when two providers are serving the exact same open weights. The model file is identical; the engine running it, the hardware it runs on, and the way requests are batched and routed are not. Those differences show up as slower first tokens, inconsistent output quality, timeouts under load, and murky data-handling policies. After putting providers through their paces, Fireworks earned our trust across all four dimensions, and we're confident bringing their stack to our users.

What Is Fireworks AI?

Fireworks AI is a production inference platform purpose-built for serving open-source models at scale. Rather than being a lab that trains its own frontier model, Fireworks specializes in one thing: running the best open-weight models — Llama, Qwen, DeepSeek, Kimi, GLM, Mistral, and more — as fast, reliably, and cost-effectively as possible.

The platform processes tens of trillions of tokens per day across 100+ hosted models, and it's the production inference layer behind well-known AI products. Cursor chose Fireworks because it's "way more performant than the open source engines." Notion cut latency from roughly 2 seconds to 350 milliseconds. Quora reported a 3x speedup in response time after migrating. That kind of engineering — custom serving stacks, optimized attention kernels, and elastic global scaling — is exactly what separates a great inference provider from a merely adequate one.

Fireworks isn't a scrappy newcomer, either — it's become one of the defining companies of the AI inference layer. In October 2025 it raised a $250M Series C at a $4 billion valuation, bringing total funding to over $327 million from an unusually deep bench of backers: Sequoia, Benchmark, Lightspeed, and Index Ventures on the venture side, plus strategic investment from NVIDIA, AMD, MongoDB, and Databricks — the chipmakers and data platforms whose stacks Fireworks sits on top of. Today it powers 10,000+ companies and hundreds of thousands of developers, with annualized revenue reported north of $280 million. When we say we picked a partner we expect to be around for the long haul, this is what we mean: Fireworks has the funding, the customers, and the infrastructure to keep serving open models reliably as the space moves.

Why We Chose Fireworks

The tweet announcing this partnership named four things that "vary a lot" in AI inference. Here's how Fireworks delivers on each:

• Quality — Serving open weights correctly is harder than it looks. Quantization choices, tokenizer handling, and sampling defaults can quietly degrade output. Fireworks runs models at production-grade fidelity so the responses you get match the model's true capability.
• Latency — Fast time-to-first-token and high sustained throughput mean snappier chats and quicker agentic loops, not just better benchmark numbers.
• Reliability — Elastic, global scaling keeps models responsive under load. Fewer timeouts, fewer failed requests, more consistent behavior when it matters.
• Privacy — Fireworks offers enterprise-grade data controls and doesn't train on customer traffic — aligning with PayPerQ's privacy-first philosophy, where conversations are stored locally by default and accounts are optional.

Major Models Fireworks Serves on PayPerQ

Fireworks hosts a deep catalog of open-source models. Here are the major families now served through PayPerQ:

Model Family	Notable Variants	Best For
Llama	Llama 3.3 70B, Llama 3.2, Llama 3.1, Llama Vision	Fast general-purpose chat, multilingual, vision
Qwen	Qwen3 (0.6B–480B), Qwen3-VL 235B, Qwen Coder, QwQ 32B	Coding, reasoning, vision-language, long context
DeepSeek	DeepSeek V4-Pro, V3.2, R1, Prover V2	Reasoning, math/proofs, cost-efficient frontier quality
Kimi	Kimi K2.7 Code, K2.6, K2 Thinking	Agentic coding, long-horizon tool use, multimodal
GLM	GLM 5.2, GLM 5.1, GLM 4.7	Agentic engineering, tool calling, long context
MiniMax	MiniMax M3, M2.7	Long-context reasoning and generation
Mistral / Mixtral	Mistral Large 3, Ministral 3, Mixtral 8x22B MoE	Efficient European-built general models
gpt-oss	gpt-oss-120B	Open reasoning and function calling
Gemma	Gemma 4, Gemma 3	Compact vision-language, many-language support

Context lengths across these models range from a few thousand tokens up to 1M tokens on the largest variants, and the lineup spans everything from lightweight fast chat to heavyweight reasoning, coding, and vision workloads. As Fireworks adds new open-weight releases — and the open-source frontier moves fast — you'll see them appear on PayPerQ.

Key Capabilities

• Access the best open-source models in one place, served on infrastructure tuned for speed and reliability
• Coding and agentic work with Kimi, Qwen Coder, GLM, and DeepSeek — strong tool use and long-horizon reasoning
• Reasoning and math with DeepSeek R1, QwQ, and gpt-oss-120B
• Vision-language tasks with Qwen3-VL, Llama Vision, and Gemma 4
• Long-context work — summarize, analyze, and reason over large documents on high-context variants

And because PayPerQ is pay-per-query, you can switch between all of these models freely and only pay for what you actually use.

What is PayPerQ?

PayPerQ is a pay-per-query AI service that gives you instant access to hundreds of chat, image, video, and audio AI models in one place. Unlike traditional ChatGPT subscription that charges $20+ per month, PPQ users pay only for what they use—averaging just $4 a month.

Account registration optional. No monthly commitments. Privacy focused. Credit cards and all major cryptos accepted. Just top up with as little as 10 cents and start using premium AI immediately.

Why Use PayPerQ?

• Access hundreds of AI models from all major providers in one place
• Pay per use - no subscriptions, no wasted money on unused credits
• No registration required - start using AI in seconds
• Start small - top up with as little as 10 cents
• Privacy-first - conversational data stored locally by default
• Average cost: ~1 cent per query

Getting Started

1. Visit ppq.ai
2. Top up your balance (crypto or credit card, as little as 10 cents)
3. Select your model and start chatting

No account creation needed—just fund and go.