Releasesby GlyphInference Serverless deprecation: MiniMax M2.5 MiniMax M2.5 is deprecated from serverless
Inference Serverless deprecation: MiniMax M2.5 MiniMax M2.5 is deprecated from serverless. Migrate to MiniMax M2.7 .
Also shipped Jun 20, 2026Fireworks AI in June 2026 →
vercel@54.14.5
Patch Changes d1e1d69: Stop prompting to install the Vercel plugin after login and link commands. 7aa52be: Show bounded progress while upgrading native and package-installed CLIs, and report when no newer version is available without running the installer. e2043e6: Build standalone Vercel CLI binaries with Node.js 24.14.1.
More from Fireworks AI platformEvery Fireworks AI platform release →
Recommended migrations
- Kimi K2.5 , migrate to Kimi K2.6 Qwen 3.6 Plus , migrate to Qwen 3.7 Plus
Training SFT learning rate scheduler documentation Documented learning rate scheduler settings for supervised...
Training SFT learning rate scheduler documentation Documented learning rate scheduler settings for supervised fine-tuning jobs, including constant , linear , and cosine schedules via firectl and the REST API lrScheduler object.
Inference Serverless deprecation: DeepSeek V4 Flash DeepSeek V4 Flash is deprecated from serverless
Inference Serverless deprecation: DeepSeek V4 Flash DeepSeek V4 Flash is deprecated from serverless. Migrate to DeepSeek V4 Flash (0731) .
Platform SSO documentation: IdP-initiated SAML Updated the Custom SSO guide
Platform SSO documentation: IdP-initiated SAML Updated the Custom SSO guide. IdP-initiated SAML is supported as an opt-in ( --enable-idp-initiated-sso ); the previous troubleshooting copy that said Fireworks only supported SP-initiated login was incorrect.
Training Serverless Training deprecation: Qwen 3.5 9B and Qwen 3.6 27B Qwen 3.5 9B and Qwen 3.6 27B are...
Training Serverless Training deprecation: Qwen 3.5 9B and Qwen 3.6 27B Qwen 3.5 9B and Qwen 3.6 27B are deprecated from Serverless Training effective August 26, 2026. Migrate new and existing Serverless Training workloads to Qwen 3.8 27B . This change applies to the shared Serverless Training pool.
Recommended migrations
- MiniMax M2.7 , migrate to MiniMax M3 GPT OSS 20B , migrate to GPT OSS 120B or Qwen3 8B for lower-latency workloads Kimi K2.6 Turbo / Fast , migrate to Kimi K2.6 (standard mode) Kimi K2.7 Code Fast , migrate to Kimi K2.7 Code (standard mode) DeepSeek V4 Pro , migrate to DeepSeek V4 Pro (0813)
Training New Serverless Training models: DeepSeek V4 Flash 0731, Qwen 3.8 27B, and Muse Glimmer 30B The...
Training New Serverless Training models: DeepSeek V4 Flash 0731, Qwen 3.8 27B, and Muse Glimmer 30B The following models are now available for LoRA workloads on the shared Serverless Training pool: DeepSeek V4 Flash 0731 with up to 262K context Qwen 3.8 27B with up to 128K context Muse Glimmer 30B with up to 128K context See the Serverless Training guide...
Inference Serverless rate limit ceilings now scale by model size Serverless adaptive rate limit ceilings now...
Inference Serverless rate limit ceilings now scale by model size Serverless adaptive rate limit ceilings now vary by model size tier. Smaller models ( Serverless rate limits for tier thresholds and ceiling values.