MegaRouter

An intelligent AI model routing platform access to 200+ mainstream models including GPT-4o, Claude, & Llama through a single API.

📧 [email protected]

[MegaRouter @MegaRouterAI]

Powerful take from Dario Amodei: AI may exceed human intelligence by 2027.

It might take a little longer — but not much.

If AI beats humans at almost everything, our economy and our sense of self-worth built on labor will be upended. #AI

[Veee @vikktorrrre]

Dario Amodei: AI could surpass human intelligence by 2027.

“I think it’s possible it could be longer than that. I don’t think it will be a whole bunch longer.”

“AI systems will be better than almost all humans at almost everything.”

“When that happens, we’ll need to have a conversation about how we organize our economy.”

“How do humans find meaning?”

“The idea that humans produce economic labor and get their sense of self-worth from it will be invalidated.”

“My true belief is that this is coming.”

[MegaRouter @MegaRouterAI]

Impressive update for DeepSeek-V4.1-Flash-1017.
Faster, stronger benchmarks, tighter outputs, better performance/cost tradeoff.

Live on web/app/API, ready for Harness, CodeBuddy & WorkBuddy integration. Users can also try it via #Megarouter.
#DeepSeeK #AI

[DeepSeek @deepseek_ai]

🚀 DeepSeek-V4.1-Flash-1017 is here!

Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.

🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model.

1/4

[MegaRouter @MegaRouterAI]

Found this peaceful hillside spot.

Sit on the bench under leafy canopies, gaze out toward the Harbour Bridge and the glistening harbour. Perfect moment to slow down and soak in the view.
#Scenery

[MegaRouter @MegaRouterAI]

As AI moves toward an agent-driven model of computing, the Router is no longer merely a gateway between an application and an AI model.
#AI #MegaRouter
https://t.co/g5ntitRUbJ

[MegaRouter @MegaRouterAI]

#CodeArena WebDev Leaderboard

MiniMax-M3.1-Flash: #12 overall | 1588 pts

Go toe-to-toe with leading frontier models for web development.

High-speed, cost-effective coding performance from #MiniMax.

[MegaRouter @MegaRouterAI]

Built for scaling AI teams.

4-tier org hierarchy, granular permission controls, shared credit pool with 3-level guardrails, plus multi-dimensional analytics. Full governance layer to manage AI spend, access & usage across your team.
https://t.co/5P3c5JGSaV
#Megarouter #AI #LLM

[MegaRouter @MegaRouterAI]

Fresh air, open views and good company — perfect day on two wheels.

Nothing beats exploring quiet countryside roads with a group of cycling buddies. #GM

[MegaRouter @MegaRouterAI]

It’s not degrees or vocabulary. It’s simply: can you predict what happens next?A raw definition of intelligence from Elon.

For AI too — impressive writing means little without accurate https://t.co/gwHpOB1vTd performance and smooth talking don’t count. Reality is the only judge.

[Kekius Maximus @kekiustop]

Elon Musk just threw out IQ scores, degrees, and fancy vocabulary in one sentence. His definition of intelligence is brutal and simple: how accurately can you predict what happens next?

Not how fast you read. Not how many books you’ve finished. Not how well you debate. Just — were you right about the future?

Think about it. A chess grandmaster sees 20 moves ahead. A great investor sees where markets go before they get there. A great engineer sees failure points before they fail. They’re not “smart” because of how they performed in school. They’re smart because reality keeps confirming their predictions.

And the same applies to AI. Elon doesn’t care how fluently a model writes or how impressive it sounds. He wants to know: does it get the future right?

By that metric, most of what we call intelligence is just confidence wearing a costume.

[MegaRouter @MegaRouterAI]

Same AI calls, drastically lower costs 🚀

✅ Single API key for all major LLMs, one unified bill
✅ Real production savings: -78% for customer service, -82% for summarization
✅ Sub-500ms auto failover, zero downtime risk when models degrade
#MegaRouter #AI

[MegaRouter @MegaRouterAI]

DeepSeek-V4.1-Flash just took the #1 spot among open models in Code Arena: WebDev — and it did it at roughly 1/10th the cost of Kimi K3.

#12 overall with 1670 points, sitting ahead of Claude Opus 5 (High) and within ~10 points of GPT-6 Sol (Max).

[Arena.ai @arena]

Exciting news: DeepSeek-V4.1-Flash-20261017 (Max) by @deepseek_ai is now the #1 open model in Code Arena: WebDev, surpassing Kimi K3 (Max) at 10x lower cost!

Highlights:
- #1 open model, ahead of Kimi K3 (Max)
- #12 overall with 1670 pts, ahead of Claude Opus 5 (High) and within ~10 pts of GPT-6 Sol (Max)
- Shifts the Pareto frontier at $0.3/$1.2 per million input/output tokens
- +52 pts vs. the previous DeepSeek-V4.1-Flash-20260910

Congrats to the @deepseek_ai team on another strong contribution to the open source ecosystem!

[MegaRouter @MegaRouterAI]

🥇 Gemini 4 Argon tops the HSS benchmark at 55.4%, narrowly beating GPT‑6‑Astra.

This test gauges AI’s ability to reason about unseen things and human behavior.

[Scale Labs @ScaleAILabs]

Congrats to @GoogleAI's Gemini 4 Argon for taking the top spot of our Humanity's Sixth Sense (HSS) benchmark with a score of 55.4%, edging out GPT-6-Astra at 53.6%. 🥇

HSS tests AI’s ability to reason beyond what’s visible, from hidden objects to predicting what happens next and understanding human behavior.

We took a closer look at performance across categories, and that’s where things get interesting. 👀🧵

[MegaRouter @MegaRouterAI]

New Artificial Analysis Decision Index ranking 🔥

Jev 1:13 leads the decision benchmark at 58 points. The chart reveals the performance-cost tradeoff for reasoning models, with Jev 1:13 on the optimal Pareto line. #AI #LLM

[MegaRouter @MegaRouterAI]

Nothing beats this twilight view from the window. Sea, clouds and the sprawling city skyline. #GN

[MegaRouter @MegaRouterAI]

Pay for what you use 🧾

No subscriptions, no minimum spend. Zero platform markup on model token rates.
✅ Free forever — no credit card needed
✅ Crypto payments supported: USDT & USDC via Gate Pay
✅ x402 Agent pay-per-call coming soon: AI agents settle requests autonomously with USDC.

Transparent pricing for your AI stack.
#Megarouter #AI

[MegaRouter @MegaRouterAI]

New top‑ranked speech‑to‑speech model incoming🔥 Grok Voice 3.0 hits 86.9 and ranks #1 on Artificial Analysis benchmark.

Building on Grok Voice 2.0, available on Realtime API for $0.08/min with solid latency.
#Grok #GPT #Gemini

[Artificial Analysis @ArtificialAnlys]

SpaceXAI’s Grok Voice 3.0 is the new leading Speech to Speech model, debuting at #1 on the Artificial Analysis Speech to Speech Index at 86.9, while also being competitive on latency

Grok Voice 3.0 is @spacexai 's successor to Grok Voice 2.0, a Speech to Speech model available through the SpaceXAI Realtime API at $0.08 per minute. We evaluated Grok Voice 3.0 with the Rex voice through the SpaceXAI Realtime API.

Key takeaways:

➤ Speech to Speech Index: Grok Voice 3.0 debuts at #1 at 86.9, ahead of GPT-Live-1 (Astra, medium) at 83.2, Gemini 3.8 Live Extended Thinking (High) at 82.6 and GPT-Live-1 (Sol, low) at 80.1. It is up on Grok Voice 2.0 at 81.3 (+5.6 points) and Grok Voice 1.0 at 73.7 (+13.2 points), released just under six months ago. The Index averages Speech Reasoning (Big Bench Audio), Agentic Performance (Tau Voice), Arena Preference, and Task Success Rate

➤ Speech Agent Arena: Grok Voice 3.0 ranks #3 in preference at Elo 1070, behind Gemini 3.1 Flash Live Minimal (1100) and Gemini 3.8 Live (1088) and ahead of GPT-Live-1 (Sol, low) at 1057, and #1 on Task Success Rate at 94.8%, highest on the board, just ahead of Grok Voice 2.0 at 94.6%. Grok Voice 2.0 trails at Elo 1011

➤ Tau Voice: Grok Voice 3.0 takes the #2 spot on our Tau Voice benchmark implementation at 71.6%, behind GPT-Live-1 (Astra, medium) at 74.5% and ahead of Gemini 3.8 Live Extended Thinking (High) at 68.6% and GPT-Live-1 (Sol, low) at 59.3% - up from 56.5% for Grok Voice 2.0

➤ Big Bench Audio: Grok Voice 3.0 scores 98.5% on audio reasoning, ahead of Gemini 3.8 Live Extended Thinking (High) at 97.7% and Grok Voice 2.0 at 97.2%

➤ Speed: Average Time to First Audio on Big Bench Audio is 0.81 seconds for Grok Voice 3.0, well ahead of GPT-Live-1 (Sol, low) at 1.24s, GPT-Live-1 (Astra, medium) at 1.34s and Gemini 3.8 Live Extended Thinking (High) at 1.35s, though slower than Grok Voice 2.0 at 0.70s

➤ Cost: Grok Voice 3.0 costs $4.80 per hour of input audio, the same as Grok Voice 2.0. That is above GPT-Live-1 (Sol, low) at $4.47 and Gemini 3.8 Live Extended Thinking (High) at $3.50, cheaper than GPT-Live-1 (Astra, medium) at $5.83, and ~2.2x cheaper than GPT-Realtime-2.1 High at $10.75

Congrats to @elonmusk and the @spacexai team 🚀

See below for more detail ⬇️

[MegaRouter @MegaRouterAI]

Unlock granular insights for all your LLM API requests.
Filter by time, team, model or API key, with CSV/PDF export.

Intelligent routing optimizes workload allocation, slashing ~40% of monthly AI spend.
#AI #Megarouter

[MegaRouter @MegaRouterAI]

A fascinating comparison from Sam Altman:
38k ChatGPT queries consume the same water as growing one CA almond.

He’s calling out the popular AI water-use myth — modern data centers’ water footprint is comparable to regular office buildings.
#SamAltman #GPT

[Veee @vikktorrrre]

Sam Altman: “For every 38,000 ChatGPT queries, that’s the same amount of water used to produce a single almond in California.”

“People eating 12 almonds at a time don’t feel like they’re doing something horrible from a water perspective.”

“Modern, very large data centers use roughly the same amount of water as an office building.”

“That’s been a robust meme and difficult to disprove, but I don’t think it holds up to any scrutiny.”

[MegaRouter @MegaRouterAI]

Nature’s good energy for the day. #GM

[MegaRouter @MegaRouterAI]

📰#MegaRouter provides a unified interface compatible with the #OpenAI API and supports access to more than 200 models through a single entry point.

Development teams can call the appropriate models at different stages of a workflow without maintaining a separate integration method for each model.
https://t.co/FO0yLozUJW

[MegaRouter @MegaRouterAI]

Big upgrade from Meta in only 6 weeks!
Muse Wonder / Muse Wonder Full score 52 & 56 on AA Intelligence Index, beating Muse Spark 1.3.

Muse Wonder on Meta API; Muse Wonder Full exclusive to Muse Code users for agent workloads.
#MUSE #AI

[Artificial Analysis @ArtificialAnlys]

Meta has released Muse Wonder and Muse Wonder Full, achieving Artificial Analysis Intelligence Index v4.3 scores of 52 and 56 at max reasoning effort - each a material gain over Muse Spark 1.3 (max) at 48, with a release gap of only 6 weeks

Muse Wonder is available for users on Meta’s first-party API, while Muse Wonder Full is currently only available for Muse Code users. Meta notes that each model is designed for personal and professional agent use

Congratulations to @AIatMeta, @finkd, and @alexandr_wang on the release!

Key Takeaways:

➤ Both models exhibit a material jump in overall Intelligence Index score. Muse Wonder Full (max) improves on Muse Spark 1.3 (max) across all ten Intelligence Index evaluations, gaining 8 points to 56. The largest gains were seen in agentic evaluations: Terminal-Bench 4.0 (+24 points, 33% to 57%), GDPval-AA v2.1 (+176 Elo, 1681 to 1857), and AA-Briefcase (+148 Elo, 1581 to 1729). Muse Wonder (max) gains 4 Intelligence Index points and lands at 52, with notable improvements vs. Muse Spark 1.3 (max) in Terminal-Bench 4.0 (33% to 52%) and AutomationBench-AA (58% to 68%)

➤ Muse Wonder Full (max) places in the top three on six of the ten Intelligence Index evaluations, and is particularly strong in agentic knowledge work and scientific reasoning. In agentic knowledge work, it narrowly leads on GDP.pdf (33%), ranks #2 on GDPval-AA v2.1 (1857 Elo), and #3 on both AA-Briefcase (1729 Elo) and AutomationBench-AA (71%). In scientific reasoning, it tops the CritPt leaderboard at 33% and ranks #3 on SciCode with 63%. This builds on the relative strengths of Muse Spark 1.3 (max), which also showed particular ability in these two domains

➤ Both models use fewer output tokens than Muse Spark 1.3 (max). Muse Wonder (max) and Muse Wonder Full (max) each use around 54k output tokens per Intelligence Index task, down ~10% from Muse Spark 1.3 (max, 60k). This usage is lower than similarly intelligent models Gemini 4 Argon (high, 62k) and Claude Fable 5.1 (max w/ fallback, 78k), but higher than GPT-6.1 Sol (max, 38k) and GPT-6 Astra (max, 27k). Muse Wonder Full (max) uses 16% fewer input tokens per Intelligence Index task than Muse Wonder (max) (6.44M vs 7.69M), meaning it is both more intelligent and more token-efficient

➤ Cost per Task for Muse Wonder (max) lands higher than most similarly intelligent models. Despite efficient output token use, premium API pricing ($4 per million input tokens, $20 per million output tokens) and high input token use (7.69M per task) push Muse Wonder (max)’s cost to $4.52 per Intelligence Index task. This is lower than Claude Fable 5.1 (max w/ fallback, $7.63), Claude Opus 5.5 (max w/ fallback, $5.98), and Claude Sonnet 5.5 (max w/ fallback, $5.46), but higher than GPT-6 Astra (max, $3.26), Gemini 4 Argon (high, $1.99), GPT-6.1 Sol (max, $0.72), and its predecessor Muse Spark 1.3 (max, $1.60). Per-token pricing is not currently available for Muse Wonder Full, so no Cost per Task figure can be estimated at this stage

➤ Both models gain significantly in Coding Agent performance. Muse Wonder Full achieves 68 on the Artificial Analysis Coding Agents Index at max effort in Muse Code, alongside Claude Code with Sonnet 5.5 (max, 68) and Opus 5.5 (max, 66). Muse Wonder (max) scores 63. These represent material gains over Muse Code with Muse Spark 1.3 (max), which scores 54

Other details for the two new models:

➤ Context windows: 1M tokens each, unchanged from Muse Spark 1.3
➤ Pricing: for Muse Wonder, $4 input / $0.20 cached input / $20 output per 1M tokens. Pricing per token is not yet announced for Muse Wonder Full
➤ Input modalities: text, image, video, and audio
➤ Output modalities: text
➤ Availability: Muse Wonder is available on Meta's first-party API and Muse Code at launch, while Muse Wonder Full is only available to Muse Code users