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Fireworks AI unveils Blackwell ultra-fast inference, Nexus Desktop and Sovereign at Forge

Announced at its first Forge conference on 3 November 2026, the lineup spans 1,500 token-per-second previews, $8 desktop model routing, trace-driven evals and customer-hosted GPU control planes.

Crimson-to-plum banner reading Fireworks unveils new products at Forge to help companies build specialized intelligence above the Fireworks mark.
Image: Fireworks AIFireworks AI’s Forge 2026 product keynote announcement.

Fireworks AI used its inaugural Forge conference on 3 November 2026 to launch inference, desktop routing, post-training and enterprise governance products aimed at running customised open-weight models in production.

In public preview on NVIDIA Blackwell GPUs, Fireworks Ultra-fast reaches up to 1,500 tokens per second on DeepSeek V4.1 Flash, trimming a 30-turn agent loop from 1 minute to 8 seconds. For non-urgent jobs, Background Mode halves standard token rates ($0.30 input and $1.20 output per million tokens standard for DeepSeek V4.1 Flash on the pricing page), paired with Multi-day Prompt Caching, generally available Elastic Burst rate limits and serverless LoRA serving via Specialized Model Inference starting with GLM 5.3 Flash.

Quality-cost scatter plot showing Ember-1 near 67% benchmark mean score at roughly $1.35 per task versus GPT-6 Astra near $3.90 and Claude Opus 5 near $6.80.
Fireworks’ Ember-1 quality-versus-cost frontier across five industry benchmarks against GPT-6 Astra and Claude Opus 5.Image: Fireworks AI

For everyday tool routing, Nexus Desktop joins the Nexus CLI inside the Codex app, Claude Desktop and OpenCode, combining open and closed models with spend tracking at $8 per month for Pro and $10 per seat per month for Teams (Team on the pricing page). On the training side, private-preview No Eval converts live inference traces and user feedback signals such as edits and retries into task evaluations and reward models, alongside free supervised, DPO and reinforcement-learning runs on Muse Glimmer 30B through 30 November 2026. For regulated organisations, private-preview Fireworks Sovereign deploys Fireworks’ control plane directly onto customer-owned cloud or data-centre GPUs, building on more than 25,000 customer-environment GPUs already under management.

Diagram showing inference traces and product signals feeding No Eval to produce a labelled training dataset and automatic reward model.
No Eval matches production traces with user thumbs, edits, retries and conversions to refresh training data and reward models.Image: Fireworks AI

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