Mia

@MiaAI_lab • 43,931 subscribers

Building with AI & LLMs // Running frontier open models locally

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Here's one way to get the most from Grok 4.5 ✨ Switching effort to "low" gives strong results on most tasks, near-zero quality loss, big usage savings — plus it's the fastest.

Here's one way to get the most from Grok 4.5 ✨ Switching effort to "low" gives strong results on most tasks, near-zero quality loss, big usage savings — plus it's the fastest.

1,312,268 次观看

People realizing they can run Opus-4.6 level intelligence on their laptop with Qwen3.8-27B. No subscription. No limits. Completely private.

People realizing they can run Opus-4.6 level intelligence on their laptop with Qwen3.8-27B. No subscription. No limits. Completely private.

167,988 次观看

My RTX 5090 is officially doing his part for local AI

My RTX 5090 is officially doing his part for local AI

23,663 次观看

DeepSeek v4.1 Flash on 3x DGX Sparks

DeepSeek v4.1 Flash on 3x DGX Sparks

30,649 次观看

One task, two models. GLM 5.3 Flash running slower at 25 tok/s prose Qwen3.8 Flash running faster at 47 tok/s prose Who will finish the task first?

One task, two models. GLM 5.3 Flash running slower at 25 tok/s prose Qwen3.8 Flash running faster at 47 tok/s prose Who will finish the task first?

27,481 次观看

Until there’s an official Grok Build app, you can still use it from your iPhone or Android with Termius (or any other SSH client). Just install Tailscale on your server, connect to the Tailscale IP in Termius, and run Grok Build from the command line as usual 👇

Until there’s an official Grok Build app, you can still use it from your iPhone or Android with Termius (or any other SSH client). Just install Tailscale on your server, connect to the Tailscale IP in Termius, and run Grok Build from the command line as usual 👇

15,627 次观看

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DeepSeek V4.1 Flash 1017 on 4x DGX Sparks runs so well, feels too good to be true. SOTA AI at home.

DeepSeek V4.1 Flash 1017 on 4x DGX Sparks runs so well, feels too good to be true. SOTA AI at home.

53,382 次观看 • 4 天前

DeepSeek V4.1 Flash 1017 on TensorFold ⚡️ - 16 concurrent session - Each with full native 1M context - Non-greedy, thinking on. OFFICIAL WEIGHTS. Recipe dropping very soon!

DeepSeek V4.1 Flash 1017 on TensorFold ⚡️ - 16 concurrent session - Each with full native 1M context - Non-greedy, thinking on. OFFICIAL WEIGHTS. Recipe dropping very soon!

21,711 次观看 • 6 天前

Whoever made this is a genius 😂

Whoever made this is a genius 😂

246,498 次观看 • 2 个月前

You'd be surprised which Claude model won this. I tested Opus 5.5, Fable 5.1, Sonnet 5.5 & Haiku 5.5. All on High effort. Who built the best Gummy Bears? 🥇 Sonnet 5.5 did the BEST by far, it's not even close. As expected, Haiku performed the worst. Opus and Fable are close, so it's a matter of personal taste. I recently claimed that Sonnet 5.5 on high is better than Opus 5.5 on med, but in here, every model is on high, and Sonnet beat them all! Live demo link below.

You'd be surprised which Claude model won this. I tested Opus 5.5, Fable 5.1, Sonnet 5.5 & Haiku 5.5. All on High effort. Who built the best Gummy Bears? 🥇 Sonnet 5.5 did the BEST by far, it's not even close. As expected, Haiku performed the worst. Opus and Fable are close, so it's a matter of personal taste. I recently claimed that Sonnet 5.5 on high is better than Opus 5.5 on med, but in here, every model is on high, and Sonnet beat them all! Live demo link below.

21,165 次观看 • 6 天前

DeepSeek v4.1 Flash via API is almost TOO fast 🤯

DeepSeek v4.1 Flash via API is almost TOO fast 🤯

139,414 次观看 • 1 个月前

DeepSeek V4.1 Flash 1017 on 4x DGX Sparks ⚡️ - Official weights on TensorFold - 8 concurrent streams with thinking on

DeepSeek V4.1 Flash 1017 on 4x DGX Sparks ⚡️ - Official weights on TensorFold - 8 concurrent streams with thinking on

22,649 次观看 • 8 天前

Kimi K3.1 Pro does Gummy Bears. Max effort. For a new, top of the line 2.8T param model that puts itself in direct comparison with Opus 5.5, this is only an 'ok' result imo. I'm not impressed. To build it, it used 2x 5h usage limits on a $39 plan 😅

Kimi K3.1 Pro does Gummy Bears. Max effort. For a new, top of the line 2.8T param model that puts itself in direct comparison with Opus 5.5, this is only an 'ok' result imo. I'm not impressed. To build it, it used 2x 5h usage limits on a $39 plan 😅

19,095 次观看 • 7 天前

GLM 5.3 Flash vs DeepSeek V4.1 Flash 1017 Can't believe we're abusing gummy bears to test models, but here we are! Both models were run locally. - GLM 5.3 Flash: my own EXL3 quant (link below) - DeepSeek V4.1 Flash 1017: official quant - Same harness.Both on Max effort. Who won?

GLM 5.3 Flash vs DeepSeek V4.1 Flash 1017 Can't believe we're abusing gummy bears to test models, but here we are! Both models were run locally. - GLM 5.3 Flash: my own EXL3 quant (link below) - DeepSeek V4.1 Flash 1017: official quant - Same harness.Both on Max effort. Who won?

32,512 次观看 • 12 天前

This is why DGX Spark prices have sky rocketed

This is why DGX Spark prices have sky rocketed

43,094 次观看 • 23 天前

Full GLM 5.3 running on 3x DGX Sparks with TensorFold Currently 24-28 tok/s on prose

Full GLM 5.3 running on 3x DGX Sparks with TensorFold Currently 24-28 tok/s on prose

49,756 次观看 • 28 天前

That Argon gummy bear video turned out to be a FAKE. I ran the prompt myself, and the results from Gemini 4 Argon is MUCH better. Opus is still better, but Argon is not bad at all. Full prompt below.

That Argon gummy bear video turned out to be a FAKE. I ran the prompt myself, and the results from Gemini 4 Argon is MUCH better. Opus is still better, but Argon is not bad at all. Full prompt below.

27,506 次观看 • 17 天前

Highly recommend to watch the whole thing and pay a special attention to the top-right of the screen.

Highly recommend to watch the whole thing and pay a special attention to the top-right of the screen.

46,133 次观看 • 1 个月前

DeepSeek v4.1 Flash running on 2x DGX Sparks

DeepSeek v4.1 Flash running on 2x DGX Sparks

59,572 次观看 • 1 个月前

Opus 5.5 built me a Fortnite replica in one prompt

Opus 5.5 built me a Fortnite replica in one prompt

44,111 次观看 • 1 个月前

Qwen3.8 Flash I really like this model and find it great for frontend. It performs much better than Qwen3.8 27B.

Qwen3.8 Flash I really like this model and find it great for frontend. It performs much better than Qwen3.8 27B.

61,327 次观看 • 1 个月前

- GLM 5.3 Flash EXL3 - 2x DGX Sparks - TensorFold - 4 concurrent prose streams Pay attention to tok/s and TTFT on each stream. Buttery smooth experience!

- GLM 5.3 Flash EXL3 - 2x DGX Sparks - TensorFold - 4 concurrent prose streams Pay attention to tok/s and TTFT on each stream. Buttery smooth experience!

32,203 次观看 • 1 个月前

Jumpgate - hyperspace jump DS4.1F-1017 vs GLM 5.3 Flash vs Fable 5.1 Who won imo: 🥇 Fable 5.1 🥈 DeepSeek V4.1 Flash 1017 🥉 GLM 5.3 Flash You can run these by yourself here: Prompt below.

Jumpgate - hyperspace jump DS4.1F-1017 vs GLM 5.3 Flash vs Fable 5.1 Who won imo: 🥇 Fable 5.1 🥈 DeepSeek V4.1 Flash 1017 🥉 GLM 5.3 Flash You can run these by yourself here: Prompt below.

12,939 次观看 • 11 天前

I ran this locally with GLM-5.3 Flash EXL3 on my DGX Sparks, and I think it beats both Fable 5.1 and GPT-6 Astra. The crazy part: it was faster to make create this on my sparks than it was with either Fable 5.1 or Astra. Live link here:

I ran this locally with GLM-5.3 Flash EXL3 on my DGX Sparks, and I think it beats both Fable 5.1 and GPT-6 Astra. The crazy part: it was faster to make create this on my sparks than it was with either Fable 5.1 or Astra. Live link here:

48,031 次观看 • 1 个月前

Check out how DeepSeek v4.1 Flash performs on 2x DGX Sparks after the update. Smooth experience!

Check out how DeepSeek v4.1 Flash performs on 2x DGX Sparks after the update. Smooth experience!

39,502 次观看 • 1 个月前

Models now include a proper filtering per device type, and consists 16 different recipes! Includes DGX Sparks, RTX 5090, RTX 6000 Pro, and 16-24 GB GPUs. Let me know what you think!

Models now include a proper filtering per device type, and consists 16 different recipes! Includes DGX Sparks, RTX 5090, RTX 6000 Pro, and 16-24 GB GPUs. Let me know what you think!

30,322 次观看 • 1 个月前