OpenRouter

Benchmarks TypeSafe's Jev decision model against GPT and Claude Opus on support triage, comparing accuracy, latency, and cost, and shows TypeScript patterns for routing with Jev, computing in code, and writing replies with an LLM.

Venice is now a provider on OpenRouter, leading with Dolphin Mistral 24B Venice Edition: a low-refusal fine-tune of Mistral 24B with no server-side storage, free to call through the API and chatroom.

Inception's Mercury Decide on OpenRouter now takes images in the Decisions request state and answers typed questions with a choice, score or probability. Pricing is unchanged and images bill as input tokens.

The arithmetic behind prompt caching in agent loops: what reads and writes actually cost per provider, why a single unreused write loses money, and why multi-provider routing quietly breaks the warm cache on turn two unless sessions are pinned.

OpenRouter's review of ByteDance's Seedance 2.5 breaks down its token-based per-second pricing (about $0.103/s at 480p, $0.231/s at 720p), 30-second clip length, image/video/audio reference inputs, and how it stacks up against Seedance 2.0, Wan 3.0, and Veo 3.1.

The OpenRouter Auto Router widens its candidate pool to 19 models chosen for quality, reports the model that actually served each request via API and UI, and pilots Not Diamond's meta model as the routing brain while access stays free.

Measured billing data from users who moved from GPT-5.4 to GPT-5.5 shows real cost rising 49 to 92 percent rather than the headline 2x, because reduced verbosity only offsets the increase on prompts above 10K tokens and reverses in the 2K to 10K range.

An argument about whether implicit prompt caching counts as retention under ZDR standards, tracing KV cache through GPU memory, host DRAM and NVMe paging, and explaining why Google classifies it as retention while most providers do not.

Cloudflare's Workers AI platform becomes an OpenRouter provider, adding edge-served open-weight options: Gemma 7B-IT with tool calling, DeepSeek R1 Distill Qwen 32B, and the Llama 3 through 3.3 line including an 11B vision model.

A method for model selection in agents: define the quality bar, run cheap, mid and frontier models on your own examples, compute cost per quality point from billed usage, and recheck as models and prices change.

OpenRouter's preset guide shows how to store a model list, system prompt, provider routing, and sampling parameters under one versioned slug (@preset/name) so every app referencing it updates when you edit the preset instead of redeploying code.

Routing splits into two independent decisions: which model answers, and which provider serves it. Every configuration knob maps to one of them. Covers the provider object, price-weighted load balancing, the throughput and cost shortcuts, fallback interaction, and where an auto router belongs.

Responses through OpenRouter now carry a normalized finish_reason following OpenAI conventions, with the provider's raw value preserved alongside as native_finish_reason. Code that switches on stop conditions works the same across models.

Fusion dispatches one prompt to a panel of models and has a judge model synthesize the responses. Across 100 DRACO deep-research tasks a Fable 5 plus GPT-5.5 panel scored 69.0 percent against 65.3 for the best solo model, and a budget panel beat both GPT-5.5 and Opus 4.8.

Models get pulled and restricted routinely, and a slug pinned in code turns that into a redeploy for every service. Covers moving model choice, fallback chains, provider rules and retention policy into a named server-side preset, and what rollback looks like once you do.

OpenRouter adds ElevenLabs Eleven v4, v4 Turbo and Scribe v2 among eleven voice models, callable with an OpenRouter key. Includes model selection guidance, character limits per request, and a 50% launch discount until October 19.

Quality-weighted provider routing becomes the default for tool-calling requests, rescoring providers every few minutes against throughput, tool-call schema validity measured across production traffic, and scheduled TauBench Verified and GPQA-Diamond runs.

Connecting the open-source OpenClaw agent runner to a model gateway: one onboarding command, the author/slug reference format with version pinning and routing suffixes, per-agent model assignment for cost control, and why server deployments must set the key in config rather than the shell.

OpenRouter documents how provider implementations of identical model weights diverge, shows benchmark spreads tightening as providers burn a model in, and introduces exacto endpoints that restrict routing to providers with measurably higher tool-calling success.

OpenRouter publishes a side-by-side image benchmark across 39 models, built on prompts chosen to break them: counting, negation, occlusion, exact typography, and minimal-diff edits. Results are visually judgeable and sortable by price and generation time.

ScaleDown's family of constrained-decoding models arrives on OpenRouter: Summarize for context compaction, Extract for schema-driven JSON with confidence and source spans, and Classify-1 with calibrated label probabilities.

Introduces TypeSafe's Jev, a System One decision model on OpenRouter that returns typed choices with calibrated probabilities across four primitives, with API examples, how to read confidence, pricing, and when to prefer it over an LLM.

OpenRouter added server-side Presets: model selection, provider routing, system prompts and generation parameters stored in the dashboard and referenced from a request as @preset/slug, with optional per-request model override.

OpenRouter's case study on Descript shows how a Claude Tag Slack integration lets anyone trigger model evals and open a PR from a Slack message, cutting the team's evaluation cycle from a week-long engineering queue to about two hours per new model.