Knowledge catalogue
Fine-tuning on your proprietary data is the highest leverage thing you can do. Prompts get copied overnight. A model trained on your data, your evals, your edge cases is a strong moat. OpenAI is windi
Frontier labs are betting AGI models will be so good you won't ever want to customize them. We think different. Building on a closed platform means renting your intelligence. The landlord sets the ter
Learn how to structure your AI stack. Our co-founder @the_bunny_chen talks with @theinfrapod's @tnachen and @ianlivingstone about inference optimization, the open vs. closed model debate, and building
We’ve been working closely with the @harvey team on the launch of the Legal Agent Benchmark, a product focused on evaluating how open-weight models perform on long-horizon, real-world legal tasks. Che
Why are four of the top 10 trending vendors AI inference platforms? Companies are getting selective about which model handles which task, and routing tokens accordingly. Read more from @arakharazian a
🤝 OpenHuman x Fireworks AI We are excited to announce one of our very first partnerships with Fireworks AI. OpenHuman is now powered by @FireworksAI_HQ: the fastest inference for Qwen3 outside of Alib
Our cofounder @the_bunny_chen joined @GregorVand to talk about open models, production inference, and how RFT is unlocking model customization for teams without a dedicated ML org. They covered custom
Qwen 3.5 from @Alibaba_Qwen is now available on @FireworksAI_HQ Training Platform across the Managed and Training API workflows. Try SFT, DPO, RL with smart defaults or your own custom loss function w
2026: the year of explosive AI innovation. @FireworksAI_HQ Co-founder & CEO Lin Qiao speaks on how the massive expansion of customized inference and models is creating speed of light production to sca
DeepSeek V4-Pro is now available on the Fireworks AI platform, likely offering accelerated inference speeds ('Zoooooom' suggests performance optimization). This deployment enables users to access Deep
Excited to support @NVIDIA Nemotron 3 Nano Omni, now available on Fireworks. It's the first open model that handles vision, audio, video, and text in a single inference loop. Built for multimodal sub-
GLM 5.1 from @Zai_org is now available on @FireworksAI_HQ Training Platform across the Managed and Training API workflows. Try SFT and DPO with smart defaults or your own custom loss function with a 2
Safe tokenization is a security feature that helps prevent prompt injection attacks by ensuring that user inputs are properly processed and isolated from system instructions. Fireworks AI discusses ho
DeepSeek V4-Pro is live on Fireworks: → Frontier-class coding and reasoning, open-weights → 1M context standard, MIT licensed → 1.74 / 3.48 per 1M tok Get started now → https://app.fireworks.ai/models
Doing the right thing might take time, but it’s worth the wait when tens of thousands of users’ production workloads depend on it. And yes, DeepSeek V4 is coming to @FireworksAI_HQ soon 👀🚀 The DeepSee
@FireworksAI_HQ deeply believes in delivering the frontier quality. We will spend all the effort giving our users and the broad community the best OSS model quality. Deepseek V4 API up anytime now aft
Gemma 4 (26B + 31B) from @GoogleDeepMind is now available on the Fireworks Training Platform across the Managed and Training API workflows. Try SFT and DPO with smart defaults or your own custom loss
Kimi K2.6 from @Kimi_Moonshot is now available on @FireworksAI_HQ Training Platform across the Managed and Training API workflows. Try SFT, DPO, RL with smart defaults or your own custom loss function
Fireworks AI posted a question to their audience asking what features or capabilities they would like to see developed next, with a specific mention of full parameter tuning as a potential option. Thi
Fireworks AI announced the release or deployment of DeepSeek V4, a large language model, alongside another project or update called 'Spud' on the same day, with the team planning to work through the n
At 30 trillion tokens a day, we're the largest inference provider outside the frontier labs' own APIs. We're hiring. Come build the infrastructure behind the top AI workloads: https://fireworks.ai/car
Props to @augmentcode for being one of the first to ship Kimi K2.6 to their users. Open models are now the frontier. Support for Kimi K2.6 is now here in Augment Code! We teamed up with @Kimi_Moonshot
Fireworks AI announced the appointment of George Hu as President of the company. The announcement came from Fireworks AI's leadership, noting that Hu and the company's founder met approximately a year
Nothing better than sprinting on a day-0 release alongside partners that run just as fast. Thank you @sarahmsachs and the @NotionHQ crew. Excited to see the day 1 reactions continue to roll in today.
Kimi has been the most popular model on Fireworks, both out of the box and as a fine-tuning base (including Composer 2) Now Kimi K2.6 is live with huge jumps (10+%) in coding, long-running agents and
We’re launching Kimi K2.6 on Fireworks as a Day-0 launch partner! K2.5 was the base for standout models like @Cursor’s Composer 2 and was the most popular model on our training platform. K2.6 on Firew
Fireworks AI published a compilation of insights on achieving training-inference parity in Mixture of Experts (MoE) models, addressing fundamental challenges in aligning model behavior between trainin
Great to be at HumanX with @Silverside_AI @LumaLabsAI and @krea_ai The SF frontier AI builder community keeps getting stronger. We're not done yet. Keep track of when and where you can meet up with th
Budget blown on closed APIs is a solvable problem. Simply replace 20m of closed-source tokens with 1m on Minimax M2.7. Frontier performance. 20x lower cost. No rate limits. If you're rethinking your A
We’re thrilled to announce @MiniMax_AI M2.7 is now available Day-0 on Fireworks for commercial use. This self-evolving agentic model delivers frontier-level performance across: → Software engineering
Best part? The spontaneous booth conversations with builders focused on turning AI ambition into production systems that scale. Open models are moving fast. The infrastructure around them is too. Grea
This week @HumanXCo was a reminder that the AI conversation has moved on. No more benchmarks vs. bubble debate. The questions were practical: → How big do you need to be to train your own model? → How
We had Lin on stage: 'the future is millions of models — one per application, one per use case.' Jet delivered a masterclass on reinforcement fine-tuning. Rob joined @WorkOS for some hot takes on the
GLM 5.1 is live on Fireworks! SOTA for agents and coding: →Plans and executes multi-hour workflows without falling apart →Planning, executing, testing, and refining over hundreds of rounds to deliver