AnyAPI.ai (@anyapi_ai) header
AnyAPI.ai (@anyapi_ai) profile picture

Unified API for ANY AI model. Memory, RAG, Smart Routing, CLI, agents and MCP integrations out of the box.

Joined June 2025
Photo by AnyAPI.ai (@anyapi_ai)Photo by AnyAPI.ai (@anyapi_ai)Photo by AnyAPI.ai (@anyapi_ai)Photo by AnyAPI.ai (@anyapi_ai)Photo by AnyAPI.ai (@anyapi_ai)Photo by AnyAPI.ai (@anyapi_ai)Photo by AnyAPI.ai (@anyapi_ai)Photo by AnyAPI.ai (@anyapi_ai)Photo by AnyAPI.ai (@anyapi_ai)Photo by AnyAPI.ai (@anyapi_ai)
we added 30 decision models to AnyAPI.ai this week: baseten: elephant-1 baseten: joey-1 baseten: mammoth-1 cloudflare: clef cloudflare: clef-flash cloudflare: clef-omni inception: mercury-decide jaredpalmer: kev-4b liquid: d1 liquid: d1-ultra liquid: d1.1 microsoft: microsoft-decision-1 nace-ai: drex-max nace-ai: drex-v1.5 nace-ai: drex-v2.0 openai: gpt-6-luna-decisions perplexity: pplx-decider-flash-v1.2 perplexity: pplx-decider-v1.2 respan: span-01 respan: span-01-lite respan: span-01-lite:free respan: span-02 scaledown: classify-1 togethercomputer: tev1-4b-experimental typesafe: jev-1.13 typesafe: jev-1.14 upstage: solar-decide upstage: solar-decide-flash typesafe: jev convai: laya
🤖 Made with AI
1
6
287
AnyAPI.ai is now a native provider in @NousResearch hermes agent. no core patches, no proxy wrapper. one plugin registers a provider profile and it shows up in the model picker next to the built-ins hermes plugins install anyapi
3
9
285
Fresh models just landed on AnyAPI openai: gpt-6.1-sol openai: gpt-6.1-sol-pro
7
153
wow!
Introducing Gemini 4 Argon – our new frontier model. It’s built for complex workflows across coding, enterprise knowledge work, and cybersecurity defense – rolling out today to a set of trusted testers through our Fairwind Program.
1
95
GPT-6 Sol beats Claude Opus 5.5 - 5x cheaper and the difference isn't even close the test: infinite zoom into the Mandelbrot set as a single self-contained HTML file - WebGL shader, multi-precision math, seamless loop cost : GPT-6 Sol: $0.07 Claude Opus 5.5: $0.35 what we saw: • Opus burned 2.7x the tokens (17.6k vs 6.6k, most of it reasoning noise) • Sol's zoom actually zooms: deep exponential dive into Seahorse Valley with plasma filaments, bloom, and a perfectly seamless 6-sec loop • Opus 5.5 whole frame slowly rotates around a murky blob while the zoom crawls 6x slower - hypnotic in the worst way • Sol's code: 2× more output per token, denser, runs smoother verdict: Claude thinks longer. GPT delivers better.
2
9
642
Fresh models just landed on AnyAPI.ai Google : Gemini 3.8 Flash Anthropic : Claude Fable 5.1 OpenAI : GPT-6 Astra DeepSeek : DeepSeek v4.1 Flash Z .ai : GLM 5.3 & GLM 5.3 Flash Meta : Muse Spark 1.3
6
188
Fable 5.1 charges 40× more than Gemini 3.8 Flash for the same task. we threw both, plus GPT-5.6 Sol, at a working V12 engine and a mechanical chronograph in three.js. same prompts, one shot, no retries. the bill: watch: Fable 5.1 $2.14 · Sol $0.08 · Gemini 3.8 Flash $0.05 engine: Fable 5.1 $1.30 · Sol $0.10 · Gemini $0.04 and here's the thing: fable's watch is genuinely the best one. the escape wheel ticks in discrete steps. the hairspring breathes at 4Hz. 341 parts under a sapphire caseback. 24,346 tokens of pure gear-ratio thinking went into it, and it shows. Gemini nails museum framing in 75 seconds flat, then paints the whole movement one shade of grey. Sol's take is clean and stylized, which means the truth: it's a facade with hands. plot twist: fable's 40× engine ships a real bug. idle RPM dips below zero and the whole frame goes black. the watch is a masterpiece. the engine, not so much. so the real answer is ugly: 40× the price buys you the physics under the dial. sometimes. which one are you picking?
1
7
285
GPT-5.6 SOL vs Claude Fable 5 vs Kimi k3 – 3d rubik's cube in @threejs the setup: one prompt in, one html file out. streamed straight through AnyAPI, no agent loop, no tools, no filesystem, just a single standalone response per model models: gpt 5.6 sol , claude fable 5 , kimi k3 prompt: a fully functional 3D Rubik’s Cube simulation in one HTML file, using Three.js via CDN, with automatic self-solving results: gpt 5.6 sol – 1.36s, 8,612 total tokens, $1.53, 825 lines claude fable 5 – 1.26s, 10,725 total tokens, $3.16, 465 lines kimi k3 – 302.99s, 36,565 total tokens, $3.27, 733 lines observations: • sol and fable both returned almost instantly; kimi took 303s on the same task • fable shipped the shortest file at 465 lines, while sol shipped the largest valid file at 825 • kimi used 4.2x the total tokens of sol and still landed in roughly the same price band as fable
3
1
15
2,375
Grok 4.5 just one-shotted a full 3D Starship landing One prompt. One HTML file. No cleanup. No extra setup. We asked @grok to build a cinematic Starship touchdown at sunrise: landing burn, deployed legs, dust, steam, Boca Chica tower, ocean horizon — the whole shot. And it actually shipped. Stats: 3 min 1 sec 14,511 tokens ~$0.09 That’s the wild part: not just a cool demo — a legit 3D landing scene, one-shot, for nine cents. People love arguing about which model is smartest. We’re starting to care a lot more about which one actually ships. cc @spacexai
1
7
232
GPT-5.6 Sol vs Opus 5 vs Qwen 3.8 Max we ran all three on two one-shot 3D hero-object prompts 1)Fabergé egg on a black background 2)vintage diving helmet on a black background results: GPT-5.6 Sol generation time: ~143s avg output: ~8 600 tokens avg cost: ~$0.34 Claude Opus 5 generation time: ~214s avg output: ~17 800 tokens avg cost: ~$0.53 Qwen 3.8 Max generation time: ~258s avg output: ~17 400 tokens avg cost: ~$0.14 the interesting part: Sol was fastest and most consistent across both prompts Opus 5 wrote the longest outputs — lots of detail, but slower(faster in terms of tps) Qwen 3.8 Max was the cheapest by a wide margin, and when it worked, the code was competitive simpler objects (diving helmet) rendered reliably for all three more complex materials (Fabergé egg) separated the models the takeaway: Sol is the practical all-rounder. Opus 5 is the detail-heavy option. Qwen 3.8 Max is the budget pick with strong potential. which model won?
1
11
528
We just pushed a performance update to AnyAPI, and everything is now sub-second. — AI streaming starts in under 1s — Dashboard/catalog loads in ~0.5s — API latency is down to ~150ms One API, every major model, SOC 2 and ISO 27001 compliant. Built for production, without the latency.
4
137
Kimi K3 LIVE on AnyAPI We gave Kimi K3 one prompt: build a 3D Duck Hunt remake in a single HTML file. 9,582 tokens | ~130s | $0.14 What it built: - 3D pixel-art ducks launching from bushes - Depth-layered sky and grass field - Working crosshair with fall animations on hit - The classic 8-bit dog popping up, laughing on misses No assets. No dependencies. One file. One prompt. Docs, guides below:
4
5
2
18
2,052
GPT-5.6 Sol vs Fable 5 vs Opus 4.8 Built a Boeing 777 GE90 turbofan engine cutaway animation in a single HTML file. Parameters: Output size, generation time, token usage, cost. Results: Sol: 28 775 chars | 641s | 11 181 tokens | $0.33 Fable: 19 186 chars | 255s | 21 288 tokens | $1.04 Opus: 13 178 chars | 77s | 7 716 tokens | $0.18 Opus fastest, Sol heaviest output, Fable most expensive.
11
8
1
137
40,985
GPT-5.6 Sol , Luna , Terra LIVE on AnyAPI We gave Sol, Luna, and Terra the exact same prompt: animate a cutaway of the legendary Soyuz RD-108 rocket engine inside a single HTML file. Performance & costs: Sol: 14.5k tokens | 118s | $0.42 Luna: 5.5k tokens | 48s | $0.03 Terra: 9.0k tokens | 48s | $0.125 Sol is the powerhouse : 36KB of code, turbopump spinning, mach diamonds in the exhaust, the full museum treatment. Terra balances speed, quality, and cost right down the middle. Luna is comically cheap: three cents for a working engine breakdown. Docs, guides below:
4
2
54
18,112
Fable 5 is back on AnyAPI We gave Sonnet 5 and Fable 5 the exact same prompt: explain how the legendary 2JZ engine works and turn it into an animated, interactive 3D breakdown inside a single HTML file. Performance & Costs: Sonnet 5: 37.2k tokens | 400 sec | $0.37 Fable 5: 18.8k tokens | 238 sec | $1.01 (inc. 2k reasoning) Sonnet 5 optimized for cost, while Fable 5 cut the generation time almost in half. Honestly, both models did an absolute hell of a job rendering the engine mechanics. We'll leave it up to you to decide which output wins : let us know in the comments. Docs, guides below:
2
1
26
3,836
we’ve recently added support for the following models: OpenRouter Fusion Nex N2 Pro Nvidia Nemotron 3 Ultra 550B Nvidia Nemotron 3 Ultra 550BQwen 3.7 Plus MiniMax M3 Step 3.7 Flash Claude Opus 4.8 Fast Claude Opus 4.8 Qwen 3.7 Max Grok Build 0.1 Gemini 3.5 Flash
4
463
The first Mythos - class model just landed on AnyAPI. Fable 5 is live. But don't take our word for it. Run your own prompt against GPT-5.5 and Opus 4.8 and see what Mythos-class actually means. All three models, one key, one place.
1
3
173
Introducing Gemma-4-31B-it-Pearl on AnyAPI Pearl Research Labs’ instruction-tuned checkpoint of Gemma 4 31B is now live, powered by the @prlnet Proof of Useful Work protocol. Experience fast, decentralized AI inference via our seamless API. Driven by Pearl Research Labs, this integration bridges ML and blockchain. Every API request utilizes a decentralized network where nodes run the model and mine $PRL through their innovative PoUW mechanism.
8
491
did you know Claude Code can run on *any* AI model? set ANTHROPIC_BASE_URL to your API aggregator ( AnyAPI , OpenRouter , Together AI , etc.) boom - now you've got Kimi K2.6 , GPT-5.5 , Gemini 3.5 , DeepSeek V4 , Llama 4 running through Anthropic's agentic terminal switch models mid-session with /model, no restart needed
1
326
Grok 4.3 is now available on AnyAPI @xai fastest and most capable model to date, ranking #1 in agentic tool calling, instruction following, and enterprise domains like case law and corporate finance. 1M context! One API key, every model: anyapi.ai
2
387