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Fine-tuning to production inference is the gap where teams get stuck. At #MSBuild today, our own Rob Ferguson, @danielhanchen (@UnslothAI) and @marksaroufim (@coreautoai) discuss: model customization

Frontier models are powerful advisors. On @harvey's Legal Agent Benchmark, a GLM 5.1 worker using Claude Opus 4.7 as a sparse advisor reached 18/100 all-pass versus 14/100 for Opus alone, at 39% of th

MiniMax M3 arrives with MiniMax Sparse Attention (MSA), 15.6x faster decoding at 1M tokens. We're partnering with @MiniMax_AI to power the inference behind this week's launch. Head to http://minimax.i

Working with @FireworksAI_HQ to make MAI models easy to fine-tune and fully yours. Microsoft MAI models. Coming soon to Fireworks. Intelligence you control. End-to-end lineage you can prove. Fine-tune

Microsoft MAI models. Coming soon to Fireworks. Intelligence you control. End-to-end lineage you can prove. Fine-tune MAI reasoning models for your enterprise tasks. Your data. Your custom models. You

Move from test to production by running high-performance inference directly on Foundry. At #MSBuild, we demoed an end-to-end workflow showing how unified infrastructure improves latency, reduces cost,

Super excited to announce seven new world-class MAI models today. They represent what we consider a new era in AI designed to keep you in control and on the frontier. First is our text foundation mode

We’re looking forward to seeing how developers and enterprises use Fireworks AI on @Microsoft Foundry to power the next generation of intelligent applications. Catch us at booth F111 at #MSBuild and s

Many research labs only consider inference efficiency after the fact. Step 3.7 Flash is a 196B MoE model, and built for inference from the start by @StepFun_ai. Multi-Matrix Factorization Attention (M

Production AI systems require fundamentally different infrastructure approaches as workloads scale, with demands that differ significantly from development or testing environments. Fireworks AI discus

Another proof point for the open-weights thesis. From @RampLabs: 'If we built this again, we'd lean more on open-weight models.' Ramp pointed 10K agents at their own backend. Kimi K2.6 and DeepSeek V4

Reliability shouldn't require reserving GPUs. Serverless 2.0 is live on Fireworks: one API, 3 serving paths. → Standard: elastic default → Priority: sheds last under congestion, pricing ~1.5x standard

This tracks. 30 trillion tokens a day on our end, and open model share keeps climbing. Our partners @FactoryAI are seeing what we're seeing. Narrative violation: Open model use in Factory has more tha

10/ The bigger point: your product is the best RL environment you'll ever have. Frontier labs ship models that are good at everything. The opportunity is a model that's great at your thing. Product, u

9/ Real-time RL is where it gets fun. Catch live signals from real users on real generations. Update continuously. Ship a new version every few hours. Only works if the base model is already good enou

Fireworks is coming to Tech Week, and we're doing it across multiple cities. Boston is up first. We're co-hosting a Founder Skybar Social with @fin_ai and @TrustVanta. Follow along via #BOSTechWeek In

Cursor's new Composer 2.5 takes third on the Artificial Analysis Coding Agent Index and is ~10-60x lower cost than the higher-effort Opus 4.7 and GPT-5.5 variants above it. This release puts Composer

Fine-tuning used to mean a team, a GPU cluster, and weeks of iteration. Now it's just a CLI command, ~10 min of GPU time, a few cents of compute. You walk away owning the weights. Open models off the

Nathan's @cursor_ai team didn't prompt-engineer their way to Composer 2.5. They trained it. The massive RL program runs RL rollouts on Fireworks, alongside production inference. 'Comment 🔥 to see my p

Fireworks is coming to Tech Week First up: Boston. We're co-hosting a rooftop founder social with @fin_ai and @TrustVanta — curated crowd, real conversations, limited space. Thu May 28 · 7–10pm · #BOS

We ran 720 browser agent tasks with @nottecore across frontier models. One baseline model produced malformed outputs in ~1 out of every 5 calls, leading to retries inside multi-step workflows. Across

Not all the good stuff at Build happens on the main stage. Join Microsoft for Startups on June 2 for Dev Your Own Way. Hands-on activations with @GitHub, @FireworksAI_HQ and @NVIDIAforStartups. Real c

The @cursor_ai team shipped Composer 2 and now Composer 2.5 on the same Kimi K2.5 base model. Performance benchmarks are📈. Frontier quality and open-source economics. 85% of the compute powering these

a new era of hackathons: 2005→ look what i built with web search 2016 → can you build a rails app in 24 hrs? 2025 → spin up a CX bot with Claude in 5 min 2026 → train your own model over a weekend hap

Fireworks AI posted about a billboard at their headquarters, likely showcasing their company branding, a product announcement, or marketing campaign. The post appears to be promotional content shared

free to start. fast on day zero. proud to power the default model for LangSmith Fleet. happy building. LangSmith Fleet now has a free model powered by @FireworksAI_HQ for Developer and Plus plans. It’

Weekends are for vibe coding. But are your vibes continuously improving? Fine-tune your own model → stop waiting on someone else's release cycle. Today's training update: Gemma 4 Dense is now availabl

Fireworks Training Platform continues to expand. Today GLM 5.1 LoRA RL is now live via Training API: SFT, DPO, and full RL on a 200K context window → custom loss functions or smart defaults. No usage

If you're calling a third-party API, your competitor can make the same call tomorrow. @lqiao is the keynote speaker at @pycon tomorrow, breaking down how to build a durable moat using fine-tuned model

Kimi K2.6 and DeepSeek V4 Pro are now GA on @FireworksAI_HQ on Foundry + PTU support in the US Data Zone—predictable performance, data residency, enterprise SLAs. Frontier open models. Azure controls.

Like any AI dev not employed by a closed lab, we share the ambition that at least 10x more should be capable of training frontier models in 2026. And like we all know, some 10x leaps can't survive a c

Most teams can pick frontier models. Fewer can run them at production scale without hitting constraints in latency, throughput, and governance. Fireworks AI on @Azure AI Foundry provides the inference

𝐅𝐮𝐥𝐥-𝐏𝐚𝐫𝐚𝐦 𝐑𝐋 𝐧𝐨𝐰 𝐚𝐯𝐚𝐢𝐥𝐚𝐛𝐥𝐞 𝐟𝐨𝐫 𝐊𝐢𝐦𝐢 𝐊𝟐.𝟔 You've been told only 3 AI labs matter. The best AI apps never believed that. @cursor_ai, @vercel, @genspark_ai don't run only off-the-shelf models. They trai

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