@InfronAI

AI inference for growing businesses—from serverless APIs to custom inference solutions. 400+ models. 99.9% SLA. 24/7 technical support

 San Mateo, California, US
infron.ai/
Joined June 2025
  • Tweets551
  • Following46
  • Followers1.2K
287Media
Really glad to be working with @alibaba_cloud. Looking forward to what we build together from here, and to giving our clients a better and more rigorous service!
Alibaba Cloud
@alibaba_cloudJul 30
AI models evolve weekly. Your infra shouldn't have to. With Alibaba Cloud, @InfronAI scales open-source models like Qwen with dedicated capacity across 5 global regions, provisioned in days with verifiable placement. Read now: click.alibabacloud.com/m/200… #Qwen #AI #LighthouseCustomerStories
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Kimi K3 is built for the work that rarely fits in one prompt: large-repo coding, tool use, debugging, and long-horizon agents that iterate across images, logs, tests, and runtime feedback. Try it: infron.ai/models/moonshotai/… #infrondiscounts
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GPT-6 Luna, GPT-6.1 Sol, and GPT-6 Astra are all available on Infron. Choose OpenAI or Azure. Azure Standard routes are now 25% off. GPT-6 Luna: infron.ai/models/openai/gpt-… GPT-6.1 Sol: infron.ai/models/openai/gpt-… GPT-6 Astra: infron.ai/models/openai/gpt-… #infrondiscounts
Arena.ai
@arenaOct 20
GPT-6 Luna and GPT-6.1 Sol by @OpenAI now hold 6 of the 11 spots on the Agent Arena Pareto frontier across their reasoning efforts! - GPT-6 Luna dominates below $0.10/task, claiming 3 of the 4 optimal spots with Max, Medium and Low. - GPT-6.1 Sol sets the frontier between $0.22 and $0.65/task, with the same reasoning levels on it too. This shows why test-time scaling matters. Sometimes the best move is to switch the reasoning effort, not the model, to stay at the optimal cost/performance point. With GPT-6 Astra (Max) also on the Pareto frontier, OpenAI models hold 7 of the 11 frontier spots with multiple reasoning levels. Congrats to the @OpenAI team!
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An ESP32-S3 running a language model, entirely on-device. We’ve open-sourced TinyStories inference over Wi-Fi, with SSE and a Chat Completions-compatible API subset. Blog: infron.ai/blog/esp32-llm-ser… Code: github.com/InfronAI/esp32-ll…
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GLM 5.3 is now up to 55% off on selected routes. Its 1M-token context and multilingual reasoning support coding, research, translation, and long-document workflows across regions. Try it on Infron 👀 : infron.ai/models/z-ai/glm-5.… #infrondiscounts
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Qwen3.8 Flash is trending on Infron. 📈 Usage grew 315% week over week from Oct 17 to 23. Now 50% off: infron.ai/models/qwen/qwen3.…
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Want to try a Codex-to-iPhone workflow on your own device? We open-sourced the sample app, scripts, and step-by-step setup we used to deploy it and run its UI test on a physical iPhone. ➡️ Blog: infron.ai/blog/iphone-use-wi… ➡️ GitHub: github.com/InfronAI/iPhone-U…
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You’ll need a compatible Mac, full Xcode, your own Apple signing details, Codex access, and a USB-connected iPhone. We tested it on an iPhone 13 mini. If you try it on another setup, tell us what worked and where you got stuck.
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Kimi K3.1 Pro is now on Infron. Pro for lower cost💰: infron.ai/models/moonshotai/… HighSpeed for lower latency⚡️: infron.ai/models/moonshotai/…
Kimi.ai
@Kimi_MoonshotOct 23
Meet Kimi K3.1 Pro, our most capable 3T-class model.
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6 models. $0 input. $0 output. Available FREE on Infron🎉: 
• DeepSeek V4.1 Flash
• Qwen3.8 27B Uncensored
• Qwen3.8 27B Abliterated Cyber
• Apodex 1.1 Mini
• Ling 3.1 Flash
• Atria: Dawn Preview Tool calling, JSON mode & streaming. Explore: infron.ai/models?free=true #infrondiscounts
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DeepSeek V4.1 Flash infron.ai/models/deepsee… Qwen3.8 27B Abliterated Cyber infron.ai/models/qwen/qw… Qwen3.8 27B Uncensored infron.ai/models/qwen/qw… Apodex 1.1 Mini infron.ai/models/apodex/… Ling 3.1 Flash infron.ai/models/inclusi… Atria Dawn Preview infron.ai/models/internl…
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DeepSeek V4.1 Flash 1017 scores 45 on the Artificial Analysis Intelligence Index, up 6 points. Infron offers 3 DeepSeek V4.1 Flash options: • 1017: Up to 60% off • Standard: Up to 60% off • Free: $0 token costs
Artificial Analysis
@ArtificialAnlysOct 19
DeepSeek V4.1 Flash 1017 scores 45 on the Artificial Analysis Intelligence Index, improving on DeepSeek V4.1 Flash by 6 points, and is the equal #2 open-weights model @deepseek_ai has released DeepSeek V4.1 Flash 1017, an update on their flagship model DeepSeek V4.1 Flash. On the first-party API, DeepSeek V4.1 Flash 1017 is priced at $0.30 per 1M input tokens and $1.20 per 1M output tokens during peak hours, with off-peak pricing half of peak rates, the same pricing as DeepSeek V4.1 Flash. Key results: ➤ DeepSeek V4.1 Flash 1017 makes gains in agentic capabilities, knowledge and scientific reasoning. DeepSeek V4.1 Flash 1017’s Elo rating on GDPval-AA v2.1 is 1746, an increase of 146 points from DeepSeek V4.1 Flash’s rating of 1600. On AA-Briefcase v1.1, its Elo rating increases by 150 points from 1420 to 1570. On AA-Omniscience, its non-hallucination rate is 33%, a 29-point improvement from DeepSeek V4.1 Flash’s 4%, while seeing an improvement in accuracy from 43% to 46%, pushing its overall AA-Omniscience Index score from -5 to +5. On CritPt, DeepSeek V4.1 Flash 1017 scores 24%, up from 14% for DeepSeek V4.1 Flash. ➤ DeepSeek V4.1 Flash 1017 is now the #2 open-weights model alongside GLM-5.3. With a score of 45 on the Artificial Analysis Intelligence Index, DeepSeek V4.1 Flash 1017 is behind MiMo-V2.6-Pro by only 1 point and ahead of other open-source models like Step 5 Preview and Kimi K3 (both at 44). ➤ With a Cost per Task of $0.26, DeepSeek V4.1 Flash 1017 sits in the most attractive quadrant of Capability vs. Cost. With a Cost per Task of $0.26 and Intelligence Index score of 45, DeepSeek V4.1 Flash 1017 compares favorably to GLM-5.3-Flash at $0.28 per task and a score of 42. At the same time, MiMo-V2.6-Pro (46) at $0.13 per task and GPT-6.1 Sol (medium, 48) at $0.21 per task both offer higher capability at a lower Cost per Task. Additional model details: ➤ Context window: 1M tokens (equivalent to DeepSeek V4.1 Flash) ➤ Pricing: $0.30 per 1M input tokens and $1.20 per 1M output tokens, unchanged from DeepSeek V4.1 Flash. Cache hit price of $0.006 per 1M tokens, a 98% discount ➤ Size: 552B total parameters (16B active) ➤ License: MIT ➤ Providers: Available through DeepSeek’s first-party API, @FireworksAI_HQ , @baseten, @DeepInfra , @wafer_ai , @Cloudflare and others
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Explore all 3 endpoints: → 1017 (up to 60% off) infron.ai/models/deepseek/de… → Standard (up to 60% off) infron.ai/models/deepseek/de… → Free ($0 input/output) infron.ai/models/deepseek/de… Free access requires a $5+ balance, but free usage never deducts credits. #infrondiscounts #DeepSeek
🤖 Made with AI
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See you tomorrow at Open Infra Night! luma.com/jsu2t3ad

Open Infra Night for Agent Builders #Open Source AI Week · Luma

Join Strukto.AI, Infron.AI, and XTrace for an evening on the open-source infrastructure for AI agents and models: virtual filesystems, agent tools, sandboxed…

luma.com
Infron
@InfronAIOct 19
This Thursday, we’re co-hosting Open Infra Night for Agent Builders with @struktoai and @XTrace_ai. 📅 Oct 22 · 17:00–20:30 PT 📍 San Francisco RSVP: luma.com/jsu2t3ad #OpenSourceAIWeek #infron
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MiniMax M3.1 Flash is now live on Infron ⚡
Try it: infron.ai/models/minimax/min…
MiniMax (official)
@MiniMax_AIOct 19
MiniMax M3.1 Flash: Space Performance + Bunny Speed 🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash. 💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed. API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens. Model weights will arrive on Oct 23. API: platform.minimax.io M Plan: minimax.io/m-plan MiniMax Code for desktop: agent.minimax.io/download
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We’ve open-sourced the NVIDIA DGX Spark GB10 Testing Suite. 👀 More throughput ≠ faster responses for every user. Peak specs ≠ real-world latency. Two GB10 nodes. Reproducible tests. Real-world inference benchmarks. ➡️ GitHub: github.com/InfronAI/NVIDIA-D… ➡️ Benchmark breakdown: infron.ai/blog/nvidia-dgx-sp… #Infron #Benchmark
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Infron provides Grok Imagine Image 2.0 at 20% off the listed xAI Standard rate. Text-to-image generation: $0.032 per generation, down from $0.04. Explore the model and current pricing: infron.ai/models/x-ai/grok-i… #infrondiscounts #Grok
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Excited to support AgentVFS as a sponsor. The idea of giving AI agents a familiar way to work with service through files and shell commands is really inspiring. Congrats to the team on the release, and a special thank-you to @cdxy_ and @AndrewHan_Zheng for contributing. Looking forward to seeing what the community builds with it!
Zecheng Zhang
@zechengzhOct 20
We're releasing AgentVFS, a virtual filesystem interface for AI agents agentvfs.org/ AgentVFS unifies every service into one interface and replaces the need of calling MCP. Stored data becomes one virtual filesystem across services, described by VFS.md, and actions become virtual CLIs, so the agent no longer calls MCP tools at all. AI agents work on live data across every service through the terminal-like interface they know best. They use the Unix tools they learned in training (ls, grep, jq, pipes, loops) and the terminal workflows they practiced in post-training on agentic coding. We're also releasing VFS-Bench 1.0 agentvfs.org/benchmark/vfs-b…, the first systematic study and benchmark to compare a virtual filesystem with MCP on the same tasks. Compared with MCP, AgentVFS uses up to 88% fewer tokens and has about a 5% higher success rate on average.
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173 discounted models. 13 model families. 👀 Explore the latest discounts across GPT, Gemini, Qwen, DeepSeek, GLM and more. Download the full pricing list in Excel or CSV for easy comparison. Need volume pricing? infron.ai/contact Explore discounts: infron.ai/dashboard/discount #infrondiscounts
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