Changelog
New updates and improvements
Improved
Prompt Library — Optimize any saved prompt version directly from Prompt Library. Prompt Optimizations now creates a new version automatically, preserving the original while making it easy to review and promote improvements.
Prompt Comparison with Samples — Compare the original and optimized prompt side-by-side using sample inputs before promoting a new version. Quickly validate improvements and understand how prompt changes affect model outputs.
Added
BytePlus Provider — Added support for BytePlus-hosted models. FastRouter automatically handles BytePlus' custom pricing flow, including providers that return pricing information asynchronously, ensuring accurate cost tracking and billing.
New Video & Multimodal Models — Added support for the latest image, video, and reasoning models, including x-ai/grok-imagine-video, GLM 5.2, Kimi Code 2.7, and Minimax M3.
Added
Prompt Library — Write, store, version, and optimize prompts in one place and reference them by ID in API calls, so prompt changes ship without a code deploy. Mark any version as Production to serve it to all live requests, and roll back instantly by promoting an earlier version. Optimize — Refine a stored prompt with Prompt Optimizations and save the result as a tracked, optimized version, with Compare to diff versions before promoting. Variables — Insert {{curly braces}} placeholders in a prompt and fill them per request via the variables field.
Added
Free Models (:free) — Append :free to a supported model ID (e.g. sarvam/sarvam-105b:free) to route requests at no cost, with the suffix stripped transparently before reaching the provider. Available to all orgs regardless of billing status. Per-model daily quota — 10 requests per org per day, tracked independently per model and reset daily at UTC midnight; paid orgs consume free quota rather than billing credits.
https://docs.fastrouter.ai/explore-features/free-models-free
Added
Support for non-Claude models via Anthropic Messages format — Route Claude Code requests to OpenAI, DeepSeek, and other FastRouter-supported providers using the same Anthropic-compatible interface
Universal model access in Claude Code — Launch Claude Code with any FastRouter-supported model using the --model flag, without changing tooling or workflows
Added
Bring Your Own Keys (BYOK) for external providers — Attach your own API credentials from supported LLM providers directly to FastRouter while preserving your negotiated pricing Custom model provisioning — Register fine-tuned or privately hosted models with custom endpoints, pricing metadata, and API compatibility mappings Advanced endpoint configuration — Override provider base URLs with OpenAI-, Anthropic-, or Gemini-compatible formats, plus support for custom authentication headers Granular model enablement — Enable or disable individual catalog models per integration and map custom models to provider-specific endpoints Integrated routing visibility — Reference integrations via Provider Slug across Virtual Models, Gateway Configs, and Activity Logs for full routing traceability https://docs.fastrouter.ai/add-external-keys-byok
Added
Video Evaluations for AI-generated content — Automatically assess video outputs at scale using LLM-based judges, with scoring across motion fidelity, audio-visual sync, cinematic quality, and prompt adherence
Seamless log-based dataset creation — Import video generation logs directly from FastRouter activity with filtering, sampling, and zero manual uploads
Unified evaluation infrastructure — Use the same Custom Evaluations setup as text and image evals, including shared judge configuration, scoring rubrics, and dashboards
Multimodal LLM judging — Leverage capable video-aware models to evaluate outputs with structured reasoning across multiple quality dimensions
Deep-dive result analysis — Access per-video judge reasoning, aggregated performance metrics, and cost/latency insights in a single view
Added
Flex Pricing for Vertex AI and Google AI Studio models — Access supported models at up to 50% lower cost by using provider Flex inference tiers, ideal for batch jobs, background workloads, and latency-tolerant applications
Zero code-change activation — Append :flex to any supported model ID (for example google/gemini-3.1-pro-preview:flex) while keeping the same API key, endpoint, and request payload
Provider-native Flex routing — FastRouter automatically routes requests to the provider’s discounted Flex tier, with support for provider pinning to ensure correct execution paths
Built for async and cost-sensitive workloads — Recommended for summarisation pipelines, data extraction, classification, eval runs, scheduled jobs, and large-scale preprocessing tasks where response speed is less critical
Model Catalog Flex visibility — View supported Flex-enabled models and pricing directly in the model catalog, with per-model availability across providers
Added
Flex Pricing for OpenAI models — Access supported models at up to 50% lower cost by using provider Flex inference tiers, ideal for batch jobs, background workloads, and latency-tolerant applications
Zero code-change activation — Append :flex to any supported model ID (for example openai/gpt-5.4-nano:flex) while keeping the same API key, endpoint, and request payload
Provider-native Flex routing — FastRouter automatically routes requests to the provider’s discounted Flex tier, with support for provider pinning to ensure correct execution paths
Built for async and cost-sensitive workloads — Recommended for summarisation pipelines, data extraction, classification, eval runs, scheduled jobs, and large-scale preprocessing tasks where response speed is less critical
Model Catalog Flex visibility — View supported Flex-enabled models and pricing directly in the model catalog, with per-model availability across providers
Added
Prompt Optimizations (GEPA-powered) — Automatically improve system prompts using FastRouter’s Genetic-Pareto optimization engine with iterative reflection, mutation, and scoring
Run prompt experiments from your own data — Import datasets from files or Activity Logs, evaluate against custom metrics, and compare optimized prompts against baseline performance
LLM-as-a-Judge evaluations — Score prompts across metrics like Accuracy, Helpfulness, Safety, Completeness, or your own custom criteria using a shared evaluator model
Optimization Insights — Review improvement %, final scores, accepted iterations, and the full optimized prompt in a dedicated results view
Added
MCP Gateway — Register any MCP-compatible server (GitHub, Linear, Gmail, or your own APIs) and expose its tools to any model routed through FastRouter, with centralized credential management, project-level scoping, and selective tool exposure
OAuth 2.0 & Static Header authentication for MCP servers — Securely store and inject credentials server-side across all tool calls, with support for No Auth, Static Header, and full OAuth 2.0 authorization code flow
Auto-execution mode — Set auto_execute_tools: true to let FastRouter handle the complete tool-call loop and return a final text response directly, with a configurable max_tool_rounds cap (maximum 5)
Added
Priority Routing — Route requests through models in a fixed priority order, with automatic sequential fallback for deterministic, predictable routing
Category-Based Routing — Direct requests to different model groups based on detected prompt category, with per-category sub-strategies and a configurable default fallback
https://docs.fastrouter.ai/explore-features/virtual-model-aliases
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