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Open weights just caught up to the frontier. GLM-5.2 from Z.ai tops the open-model rankings on Artificial Analysis and Arena.ai's Agent Arena. It's now live on CoreWeave Serverless Inference at $1.39 in and $4.40 out per 1M tokens. Ship more for less.

CoreWeave

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16,637 次观看 • 3 个月前 •via X (Twitter)

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This free model just beat every closed-source AI on coding benchmarks. Open weights. 6x cheaper than Opus. The labs don't want you to know it exists. > GLM-5.2 from Zai just topped Code Arena - the first open-weights model to ever hold the #1 coding spot. Not a leaked weight, not a fine-tune. A fully open model beating GPT and Claude on their own turf. It's live on Hugging Face Inference API right now. 5 providers: Novita, Together AI, Fireworks, Deepinfra, Zai. OpenAI-compatible client. → Go to huggingface(.)co → grab HF_TOKEN from account settings → plug into any OpenAI-compatible client 6x cheaper than Opus. Companies bleeding on AI bills are already routing to this for orchestration, caching, and token optimization. The smart money moved before the headline dropped. > Now you know. huggingface(.)co/zai-org/GLM-5.2 Bookmark this before everyone else figures it out.

This free model just beat every closed-source AI on coding benchmarks. Open weights. 6x cheaper than Opus. The labs don't want you to know it exists. > GLM-5.2 from Zai just topped Code Arena - the first open-weights model to ever hold the #1 coding spot. Not a leaked weight, not a fine-tune. A fully open model beating GPT and Claude on their own turf. It's live on Hugging Face Inference API right now. 5 providers: Novita, Together AI, Fireworks, Deepinfra, Zai. OpenAI-compatible client. → Go to huggingface(.)co → grab HF_TOKEN from account settings → plug into any OpenAI-compatible client 6x cheaper than Opus. Companies bleeding on AI bills are already routing to this for orchestration, caching, and token optimization. The smart money moved before the headline dropped. > Now you know. huggingface(.)co/zai-org/GLM-5.2 Bookmark this before everyone else figures it out.

Atenov int.

12,395 次观看 • 3 个月前

Here's an example of a creation by GLM 5.2 on Design Arena, made from only one prompt. Just six months ago, there was a big enough difference between open and closed weight models that we considered having two separate evaluations. Open weights have come a long way. Congrats to the Z.ai team for this achievement!

Here's an example of a creation by GLM 5.2 on Design Arena, made from only one prompt. Just six months ago, there was a big enough difference between open and closed weight models that we considered having two separate evaluations. Open weights have come a long way. Congrats to the Z.ai team for this achievement!

Grace Li

14,570 次观看 • 3 个月前

GLM 5.2 INPUT FELL FROM $1.40 TO SEVEN CENTS PER MILLION IN NINETY DAYS • what it costs now > $0.07 per million input at the cheapest of 20 providers, a 95% drop in three months. > direct still lists $1.40 in and $4.40 out, with cached input at $0.26. > Same model, same weights, twenty-fold spread depending on the door you walk through. • the free way in > New accounts on get 20M tokens: > 744B MoE, 1M context, MIT weights you can also just download and self-host. Nobody announced this. It happened one provider at a time -> and the model itself never changed. Check which provider you are actually routed through before you top up anywhere ↓

GLM 5.2 INPUT FELL FROM $1.40 TO SEVEN CENTS PER MILLION IN NINETY DAYS • what it costs now > $0.07 per million input at the cheapest of 20 providers, a 95% drop in three months. > direct still lists $1.40 in and $4.40 out, with cached input at $0.26. > Same model, same weights, twenty-fold spread depending on the door you walk through. • the free way in > New accounts on get 20M tokens: > 744B MoE, 1M context, MIT weights you can also just download and self-host. Nobody announced this. It happened one provider at a time -> and the model itself never changed. Check which provider you are actually routed through before you top up anywhere ↓

slash1s

30,276 次观看 • 1 个月前

Jensen announced on stage at #COMPUTEX2026 that we'll be among the first cloud providers to bring up NVIDIA Vera Rubin NVL72, to help accelerate the era of AI factories. As part of NVIDIA's full-stack AI factory platform, Vera Rubin NVL72 is designed to run frontier and open-source models with exceptional performance, efficiency, and scalability—delivering more intelligence per watt and lower token costs at scale. It's GO time. ⚡️

Jensen announced on stage at #COMPUTEX2026 that we'll be among the first cloud providers to bring up NVIDIA Vera Rubin NVL72, to help accelerate the era of AI factories. As part of NVIDIA's full-stack AI factory platform, Vera Rubin NVL72 is designed to run frontier and open-source models with exceptional performance, efficiency, and scalability—delivering more intelligence per watt and lower token costs at scale. It's GO time. ⚡️

CoreWeave

28,320 次观看 • 4 个月前

Our self-improving agents optimized the full @vLLM_project inference stack, with up to 16% more throughput and interactivity for DeepSeek v4 Pro and Z.ai GLM 5.2 on B200s (no MTP). Every change was verified and our agents got better and faster at it with each iteration.

Our self-improving agents optimized the full @vLLM_project inference stack, with up to 16% more throughput and interactivity for DeepSeek v4 Pro and Z.ai GLM 5.2 on B200s (no MTP). Every change was verified and our agents got better and faster at it with each iteration.

Asari AI

138,267 次观看 • 2 个月前

The first-ever measured silicon numbers for @NVIDIA Vera Rubin NVL72 are in 😲 First measured performance shows 10x more tokens per megawatt than Blackwell. No projections. Real results from live hardware.

The first-ever measured silicon numbers for @NVIDIA Vera Rubin NVL72 are in 😲 First measured performance shows 10x more tokens per megawatt than Blackwell. No projections. Real results from live hardware.

CoreWeave

488,687 次观看 • 2 个月前

MiMo-V2.6-Pro is live on Wally. Day 1. Xiaomi MiMo's new open-weights flagship, top of the Artificial Analysis Intelligence Index for open-weight models. 320 tok/s, 2.4x the model maker's own API, in <24h. 1/4

MiMo-V2.6-Pro is live on Wally. Day 1. Xiaomi MiMo's new open-weights flagship, top of the Artificial Analysis Intelligence Index for open-weight models. 320 tok/s, 2.4x the model maker's own API, in <24h. 1/4

RunAnywhere

12,600 次观看 • 15 天前

(Z.ai) is now a model provider inside TRAE. You can BYOK and add GLM-4.6 and GLM-4.5 to TRAE IDE. GLM-4.5 supports up to 128K context and GLM-4.6 expands up to 200K context. Both deliver strong coding and reasoning performance on the benchmark and offers dual “thinking/fast” modes. Available now in the latest version.

(Z.ai) is now a model provider inside TRAE. You can BYOK and add GLM-4.6 and GLM-4.5 to TRAE IDE. GLM-4.5 supports up to 128K context and GLM-4.6 expands up to 200K context. Both deliver strong coding and reasoning performance on the benchmark and offers dual “thinking/fast” modes. Available now in the latest version.

TRAE

63,629 次观看 • 11 个月前

Cerebras Code just got an UPGRADE. It's now powered by GLM 4.6 Pro Plans ($50): 300k ▶️ 1M TPM @ 24M Tokens/day Max Plans ($200): 400k ▶️ 1.5M TPM @ 120M Tokens/day Fastest GLM provider on the planet at 1000 tokens/s and at 131K context. Get yours before we run out 👇

Cerebras Code just got an UPGRADE. It's now powered by GLM 4.6 Pro Plans ($50): 300k ▶️ 1M TPM @ 24M Tokens/day Max Plans ($200): 400k ▶️ 1.5M TPM @ 120M Tokens/day Fastest GLM provider on the planet at 1000 tokens/s and at 131K context. Get yours before we run out 👇

Cerebras

177,904 次观看 • 11 个月前

Claude Opus 5, Qwen 3.8 Max, GLM-5.3-Flash, Tencent Hy4 - frontier models sitting on FREE tiers right now: > HuggingFace: Tencent Hy4-preview, 770B MoE, open weights, self-host > TokenRouter: Qwen 3.8 Max free, up to 1B tokens, no card > ZenMux: GLM-5.3-Flash free tier, rate-limited > JustWoker: $50 free credits for Claude Opus 5, API access Four paths to frontier models at $0. The paid tier is becoming the backup plan.

Claude Opus 5, Qwen 3.8 Max, GLM-5.3-Flash, Tencent Hy4 - frontier models sitting on FREE tiers right now: > HuggingFace: Tencent Hy4-preview, 770B MoE, open weights, self-host > TokenRouter: Qwen 3.8 Max free, up to 1B tokens, no card > ZenMux: GLM-5.3-Flash free tier, rate-limited > JustWoker: $50 free credits for Claude Opus 5, API access Four paths to frontier models at $0. The paid tier is becoming the backup plan.

ＺＥＦＩ

12,875 次观看 • 1 个月前

GLM-5.3 Flash Abliterated is FREE 😳 a new research version of GLM-5.3 Flash is now open for testing - 1M context window - up to 131K output tokens - 33.5 tokens/sec - free to use - OpenAI-compatible API built for coding and AI research available directly in the cloud test it here: free access is available now 👀

GLM-5.3 Flash Abliterated is FREE 😳 a new research version of GLM-5.3 Flash is now open for testing - 1M context window - up to 131K output tokens - 33.5 tokens/sec - free to use - OpenAI-compatible API built for coding and AI research available directly in the cloud test it here: free access is available now 👀

Oliver Prompts

17,923 次观看 • 3 天前

New open-source agent harness just landed! I got early access to TrueForge by TrueFoundry and have been running it locally for the past few days. The harness layer deserves as much attention as the model, and open source matters here because you can inspect the loop, run it on your own infrastructure, and swap to the latest or cheaper models. TrueForge handles the runtime work that makes an agent reliable. It drives the tool-calling loop, manages context, coordinates subagents, and executes code in a sandbox, with any model you choose. Every tool call re-sends the growing context to the model, so in practice the harness controls most of what an agent costs to run. A few things stood out from my testing and their published benchmarks. Vendor-Neutral by design. It runs OpenAI, Anthropic, and Google models alongside open-weight models like Kimi, GLM, and DeepSeek. Model routing is a setting, and you can send each task to the model that fits it. On a 14-task enterprise agent benchmark, it matched the accuracy of Claude Managed Agents running the same Opus 4.8 model at roughly 30% lower cost per run (3.8M tokens vs 10M for the same answers). Routing the same tasks to GLM-5.2 held accuracy and brought cost down by about 75%, around $3 per run instead of $12. Fully self-hosted and Open Source (MIT License). I had it running locally with one command, with sandboxed code execution working out of the box. It's time to own your agent harness. Thanks to TrueFoundry for partnering on this post.

New open-source agent harness just landed! I got early access to TrueForge by TrueFoundry and have been running it locally for the past few days. The harness layer deserves as much attention as the model, and open source matters here because you can inspect the loop, run it on your own infrastructure, and swap to the latest or cheaper models. TrueForge handles the runtime work that makes an agent reliable. It drives the tool-calling loop, manages context, coordinates subagents, and executes code in a sandbox, with any model you choose. Every tool call re-sends the growing context to the model, so in practice the harness controls most of what an agent costs to run. A few things stood out from my testing and their published benchmarks. Vendor-Neutral by design. It runs OpenAI, Anthropic, and Google models alongside open-weight models like Kimi, GLM, and DeepSeek. Model routing is a setting, and you can send each task to the model that fits it. On a 14-task enterprise agent benchmark, it matched the accuracy of Claude Managed Agents running the same Opus 4.8 model at roughly 30% lower cost per run (3.8M tokens vs 10M for the same answers). Routing the same tasks to GLM-5.2 held accuracy and brought cost down by about 75%, around $3 per run instead of $12. Fully self-hosted and Open Source (MIT License). I had it running locally with one command, with sandboxed code execution working out of the box. It's time to own your agent harness. Thanks to TrueFoundry for partnering on this post.

elvis

11,303 次观看 • 1 个月前

1/ Introducing Glider - the smallest model to beat GPT-4o-mini on eval tasks ⚡🚀 - Open source, open weights, open code - Explainable evaluations by nature - Trained on 183 criteria and 685 domains Try it out for free at 🔥

1/ Introducing Glider - the smallest model to beat GPT-4o-mini on eval tasks ⚡🚀 - Open source, open weights, open code - Explainable evaluations by nature - Trained on 183 criteria and 685 domains Try it out for free at 🔥

PatronusAI

14,879 次观看 • 1 年前

HappyHorse 1.0 is now on OpenArt 🐎 It's the #1 ranked text-to-video model on Artificial Analysis right now. Generate up to 15 seconds 1080p video with synchronised audio in a single pass and support for 7 languages.

HappyHorse 1.0 is now on OpenArt 🐎 It's the #1 ranked text-to-video model on Artificial Analysis right now. Generate up to 15 seconds 1080p video with synchronised audio in a single pass and support for 7 languages.

OpenArt

2,310,394 次观看 • 5 个月前

I watched Ox Alpha top OpenRouter for a week with no name on it. Now it's GLM-5.3-Flash, and four platforms still give it away FREE: > MIT weights, self-host. 320B, runs on multi-GPU > free coding tier, 1M tokens/day, 500 requests > free API, no card. Full 320B model at $0 > official chat from the lab that built it The stealth preview ended. The free access didn't.

I watched Ox Alpha top OpenRouter for a week with no name on it. Now it's GLM-5.3-Flash, and four platforms still give it away FREE: > MIT weights, self-host. 320B, runs on multi-GPU > free coding tier, 1M tokens/day, 500 requests > free API, no card. Full 320B model at $0 > official chat from the lab that built it The stealth preview ended. The free access didn't.

ＺＥＦＩ

16,114 次观看 • 1 个月前

Registration for #FullyConnected26 is open: 🗓️ September 29 – Oct 1 📍San Francisco 3 days and 3 tracks to accelerate the superintelligence loop. 2,000+ AI Leaders in the room. This is where you need to be.

Registration for #FullyConnected26 is open: 🗓️ September 29 – Oct 1 📍San Francisco 3 days and 3 tracks to accelerate the superintelligence loop. 2,000+ AI Leaders in the room. This is where you need to be.

CoreWeave

15,136 次观看 • 4 个月前

Fusion is the most efficient frontier harness for GPT 6 Astra and Claude Fable 5.1. You can also configure everything about it: • Base model: Fable, Astra, Sol, or Opus • Sidekick model: SWE (Free), Luna, Sol, GLM (Free) • Speed: Normal or Fast ⚡ • Reasoning level It retains Claude Fable 5.1 and GPT-6 Astra performance while reducing costs and is the first time a multi-model coding agent has been included on the Artificial Analysis Coding Agent Index! Importantly: it's also fun to use :)

Fusion is the most efficient frontier harness for GPT 6 Astra and Claude Fable 5.1. You can also configure everything about it: • Base model: Fable, Astra, Sol, or Opus • Sidekick model: SWE (Free), Luna, Sol, GLM (Free) • Speed: Normal or Fast ⚡ • Reasoning level It retains Claude Fable 5.1 and GPT-6 Astra performance while reducing costs and is the first time a multi-model coding agent has been included on the Artificial Analysis Coding Agent Index! Importantly: it's also fun to use :)

nader dabit

805,687 次观看 • 26 天前

This model is insane at design. I asked GLM 5.2 (left) and Opus 4.8 (right) to build me a landing page and you can't even tell the difference. GLM cost $0.06 while opus cost $0.49. More than 6x cheaper while being faster + more token efficient. Another win for open source AI.

This model is insane at design. I asked GLM 5.2 (left) and Opus 4.8 (right) to build me a landing page and you can't even tell the difference. GLM cost $0.06 while opus cost $0.49. More than 6x cheaper while being faster + more token efficient. Another win for open source AI.

Hassan

1,582,888 次观看 • 3 个月前

$0.04 per 1M input tokens 128K context #1 on the Decision Index sub-second decisions Drex is looking less like “another small model” and more like an actual decision layer for agents and LLMs especially if you don’t want to burn a huge model’s tokens just deciding what should happen next

$0.04 per 1M input tokens 128K context #1 on the Decision Index sub-second decisions Drex is looking less like “another small model” and more like an actual decision layer for agents and LLMs especially if you don’t want to burn a huge model’s tokens just deciding what should happen next

draven

27,308 次观看 • 7 天前

Big win for open-source LLMs! DeepSeek V4 Pro holds the top open-weights score on SWE-bench Verified, in the GPT-5.5 range. GLM 5.2 leads the open-weight intelligence index and sits near the closed frontier on long-horizon coding. But this leaderboard number is a weak proxy for real performance. It comes from one task set, run through one harness, served at one precision. The same weights can even score differently across providers, since many hosts quantize activations to fp8 and drift the model off its reference weights. Real performance is determined based on whether a model can read a repo, make coordinated edits across files, run the tests, and recover when one breaks. By that measure, the top open models hold up, but only inside the right harness. The teams that actually put DeepSeek V4 into production pipelines as a frontier substitute got there through the harness they built around the model, not by picking a stronger model. If you want to see this in practice, Cline (64k+ stars) has actually built that harness around open models, tuned so they run at production quality. And it's tuned so that these LLMs can run at production quality, with plan and act modes, checkpoints, and terminal feedback. ClinePass is the new access layer on top of it. It runs a curated set of those models inside Cline, narrowed to the ones tested for coding-agent use, with 2 to 5x the standard rate limits and no separate provider accounts, keys, or billing to track. The video below shows the setup, and I worked with the team to put this together. It runs alongside custom keys and local models as well, not in place of them.

Big win for open-source LLMs! DeepSeek V4 Pro holds the top open-weights score on SWE-bench Verified, in the GPT-5.5 range. GLM 5.2 leads the open-weight intelligence index and sits near the closed frontier on long-horizon coding. But this leaderboard number is a weak proxy for real performance. It comes from one task set, run through one harness, served at one precision. The same weights can even score differently across providers, since many hosts quantize activations to fp8 and drift the model off its reference weights. Real performance is determined based on whether a model can read a repo, make coordinated edits across files, run the tests, and recover when one breaks. By that measure, the top open models hold up, but only inside the right harness. The teams that actually put DeepSeek V4 into production pipelines as a frontier substitute got there through the harness they built around the model, not by picking a stronger model. If you want to see this in practice, Cline (64k+ stars) has actually built that harness around open models, tuned so they run at production quality. And it's tuned so that these LLMs can run at production quality, with plan and act modes, checkpoints, and terminal feedback. ClinePass is the new access layer on top of it. It runs a curated set of those models inside Cline, narrowed to the ones tested for coding-agent use, with 2 to 5x the standard rate limits and no separate provider accounts, keys, or billing to track. The video below shows the setup, and I worked with the team to put this together. It runs alongside custom keys and local models as well, not in place of them.

Avi Chawla

44,124 次观看 • 3 个月前