Fireworks AI
PulseAugur coverage of Fireworks AI — every cluster mentioning Fireworks AI across labs, papers, and developer communities, ranked by signal.
- 2026-06-12 product_launch Fireworks AI launched inference infrastructure for the MiniMax M3 model. source
- 2026-06-04 research_milestone Fireworks AI was recognized on Redpoint's InfraRed 100 list. source
- 2026-06-03 product_launch Fireworks AI's inference infrastructure has become generally available on Microsoft Azure Foundry. source
- 2026-06-03 product_launch Fireworks AI demonstrated new system-level techniques for improving AI performance and cost-efficiency on legal tasks. source
- 2026-06-02 product_launch Fireworks AI demonstrated its inference infrastructure integrated with Palantir Foundry at Microsoft Build. source
- 2026-06-02 partnership Fireworks AI announced an upcoming integration with Microsoft's MAI models. source
- 2026-06-02 partnership Fireworks AI partnered with Microsoft Foundry to enable developers and enterprises to build intelligent applications. source
- 2026-05-29 product_launch Fireworks AI launched a new inference infrastructure product. source
- 2026-05-29 product_launch NVIDIA CEO Jensen Huang referred to Fireworks AI as the "TSMC of AI factories" at GTC 2026. source
- 2026-05-29 product_launch Fireworks AI's inference infrastructure demonstrated its capability by identifying vulnerabilities using open-weight models. source
- 2026-05-29 product_launch Fireworks AI launched its Serverless 2.0 platform with new serving tiers. source
- 2026-05-27 product_launch Fireworks AI announced achieving $800 million in annualized recurring revenue. source
- 2026-05-21 product_launch Fireworks AI released Composer 2.5, an updated inference infrastructure for its coding agent. source
- 2026-05-20 research_milestone Fireworks AI published a benchmark analyzing the execution reliability of AI models in agentic tasks. source
- 2026-05-18 product_launch Fireworks AI released Composer 2 and Composer 2.5, built on the Kimi K2.5 base model.
20 day(s) with sentiment data
Fireworks AI's inference infra proves effective in identifying vulnerabilities in open-weight models
Fireworks AI's inference infrastructure has demonstrated its capability to find 7 high-severity vulnerabilities in Ramp Labs' backend using open-weight models. This suggests their infrastructure is robust and effective for security testing, potentially offering a cost-effective alternative to traditional methods.
Fireworks AI's Serverless 2.0 caters to diverse inference needs with tiered service levels
The launch of Serverless 2.0 with Standard, Priority, and Fast tiers indicates Fireworks AI is addressing a spectrum of inference demands, from general use to high-throughput agent applications. This tiered approach likely enhances user control over performance and cost, making their platform more versatile.
Fireworks AI to announce strategic partnership with NVIDIA following CEO's endorsement
NVIDIA CEO Jensen Huang referred to Fireworks AI as the 'TSMC of AI factories.' This strong endorsement, especially coming from a key player like NVIDIA, suggests a potential for a deeper strategic partnership, possibly involving deeper integration or co-development of future AI hardware/software solutions.
Fireworks AI's Serverless 2.0 tiers cater to diverse agentic workloads
The launch of Fireworks AI's Serverless 2.0 with Standard, Priority, and Fast tiers suggests a strategic focus on supporting the varied demands of agentic applications. The 'Fast' tier, in particular, seems designed for the high-throughput, low-latency requirements often seen in real-time agentic systems, while 'Priority' may handle complex, multi-turn interactions.
Fireworks AI to release a solution for LLM numerical drift
Given Fireworks AI's recent identification of numerical drift issues in LLM training vs. serving, it's plausible they will release a product or feature to address this. This could involve new libraries, model architectures, or serving optimizations designed to ensure numerical parity and maintain model integrity, especially for RLHF applications.
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Fireworks AI enables training of trillion-parameter MoE models
Fireworks AI has developed a new training infrastructure that enables the fine-tuning of trillion-parameter Mixture-of-Experts (MoE) models, overcoming previous memory and orchestration bottlenecks. This platform was in…
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Fireworks AI to showcase inference infra at Microsoft Build side event
Fireworks AI, an inference infrastructure company, is participating in Microsoft's "Dev Your Own Way" event on June 2. This event is part of Microsoft's Build conference, highlighting that significant developments can o…
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Fireworks AI spurs AI development with hackathon sponsorship
Fireworks AI is sponsoring hackathons to encourage the development of AI applications. The company envisions a future where individuals can train their own AI models over a single weekend, building on the rapid progress…
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Fireworks AI enables 256K context fine-tuning for Gemma 4 Dense
Fireworks AI has announced updates to its training infrastructure, enabling users to fine-tune models with a 256K context window. This update supports full parameter and LoRA RL training methods, including SFT and DPO. …
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PyCon US 2026 explores AI infrastructure and open-source contributions
PyCon US 2026 featured discussions on AI infrastructure, model feedback loops, and fine-tuning during its opening keynote by Lin Qiao of Fireworks AI. Additionally, a presentation focused on AI-assisted contributions an…
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Fireworks AI launches fast, free inference infrastructure
Fireworks AI has launched a new inference infrastructure service designed for speed and cost-effectiveness. The service is free to start and aims to provide rapid performance from day one. It is already powering the def…
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Fireworks AI offers Kimi K2.6 and DeepSeek V4 Pro on Azure
Fireworks AI has announced that Kimi K2.6 and DeepSeek V4 Pro models are now generally available on its platform. These models are accessible via Azure Foundry and include PTU support within the US Data Zone, promising …
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Fireworks AI Training Platform adds GLM 5.1 LoRA RL fine-tuning
Fireworks AI has launched its Training Platform, now supporting GLM 5.1 LoRA RL fine-tuning. The platform offers SFT, DPO, and full RL capabilities with a 200K context window. Users can leverage custom loss functions or…
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Fireworks AI offers inference infrastructure on Azure
Fireworks AI is offering its inference infrastructure on Azure AI Foundry, aiming to help teams run frontier models at production scale. This solution addresses common constraints in latency, throughput, and governance …
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Fireworks AI partners with LangChain for agent inference infrastructure
Fireworks AI is partnering with LangChain to provide inference infrastructure for advanced agents. The collaboration was highlighted at the Interrupt 2026 conference in San Francisco. This partnership aims to support th…
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Fireworks AI touts custom models for competitive advantage
Fireworks AI is emphasizing the importance of building a competitive advantage through custom-tuned models and efficient feedback loops. The company suggests that relying solely on third-party APIs leaves businesses vul…
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Fireworks AI targets 2026 for 10x frontier model training infrastructure
Fireworks AI is working on inference infrastructure to enable more AI developers to train frontier models by 2026. The company emphasizes its commitment to shipping production-ready solutions, suggesting a focus on reli…
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Fireworks AI enables custom training for Kimi K2.6 models
Fireworks AI has released full-parameter reinforcement learning for Kimi K2.6, enabling custom model training. This move supports companies like Cursor, Vercel, and Genspark that train open-source models on proprietary …
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Innovative Solutions boosts AI service delivery with Fireworks AI
Innovative Solutions, an AWS Premier Partner, has redesigned its enterprise services delivery by adopting Fireworks AI as its primary inference layer. This strategic shift addresses escalating AI inference costs and del…
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Fireworks AI introduces new features to prevent prompt injection attacks
Fireworks AI has introduced a new feature called safe_tokenization designed to prevent prompt injection attacks. This security measure aims to protect users' systems by ensuring that malicious inputs cannot compromise t…
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Fireworks AI offers GLM 5.1 with 200K context for agentic coding
Fireworks AI is now offering GLM 5.1 through its training platform. This model supports both managed and training API workflows, allowing users to fine-tune with custom loss functions or smart defaults. GLM 5.1 features…
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Fireworks AI hosts panel on enabling and using agents at work
Fireworks AI is hosting a panel discussion on May 7th about the use of Agents at Work. The event will feature a moderator and several panelists discussing how startups are enabling and utilizing this technology.
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Fireworks AI adds Google's Gemma 4 models to its training platform
Fireworks AI has announced the integration of Google DeepMind's Gemma 4 models, specifically the 26B and 31B parameter versions, into its training platform. This integration allows users to leverage the Fireworks Manage…
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Fireworks AI launches DeepSeek V4-Pro for inference infrastructure
DeepSeek V4-Pro, a new large language model, has been made available on the Fireworks AI inference platform. This release allows users to access and utilize the capabilities of the DeepSeek V4-Pro model through Firework…
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Fireworks AI ensures production workloads run smoothly with inference infrastructure
Fireworks AI has announced a significant upgrade to its inference infrastructure, emphasizing reliability and performance for production workloads. The company highlighted that these improvements, while potentially time…