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🚨 Same sales data. Same prompt. ~32% estimated lower cost. I put the exact same analysis through: Claude Opus 4.8 → $0.12 vs. GMI Router → Cost Mode → Gemini 3.7 Flash → ~$0.081 The task wasn't simple: 6 months of sales data across 4 products → trends, product... show more

Altiam Kabir

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32,603 просмотров • 2 месяцев назад •via X (Twitter)

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🚨 GMI estimated ~$0.11 in savings on one 3-step Python coding workflow. I gave GMI Router the same e-commerce codebase and split the work into 3 requests: 👉 Code analysis → Cost Mode → DeepSeek-V4-Flash → ~$0.046 saved 👉 Debugging → Balanced Mode → DeepSeek-V4-Flash → ~$0.042 saved 👉 Implementation + testing → Quality Mode → DeepSeek-V4-Flash → ~$0.019 saved Total: ~$0.11 estimated savings vs Claude Opus 4.8, based on GMI's estimated token usage. But here's what caught my attention: Router selected the same model for all 3 tasks — even though I changed the mode each time. And that's actually the point. GMI Cloud 's Router is cache-aware. When the same model can handle the next request, sticking with it can help preserve cache reuse and reduce cost. There's another reason: These tasks weren't especially difficult. So even in Quality Mode, Router didn't need to move to a heavier model. The result: 1 codebase. 3 tasks. 3 routing modes. 1 lightweight model. ~$0.11 estimated savings. This is why request-level routing is more interesting than simply assigning a different model to every task.

🚨 GMI estimated ~$0.11 in savings on one 3-step Python coding workflow. I gave GMI Router the same e-commerce codebase and split the work into 3 requests: 👉 Code analysis → Cost Mode → DeepSeek-V4-Flash → ~$0.046 saved 👉 Debugging → Balanced Mode → DeepSeek-V4-Flash → ~$0.042 saved 👉 Implementation + testing → Quality Mode → DeepSeek-V4-Flash → ~$0.019 saved Total: ~$0.11 estimated savings vs Claude Opus 4.8, based on GMI's estimated token usage. But here's what caught my attention: Router selected the same model for all 3 tasks — even though I changed the mode each time. And that's actually the point. GMI Cloud 's Router is cache-aware. When the same model can handle the next request, sticking with it can help preserve cache reuse and reduce cost. There's another reason: These tasks weren't especially difficult. So even in Quality Mode, Router didn't need to move to a heavier model. The result: 1 codebase. 3 tasks. 3 routing modes. 1 lightweight model. ~$0.11 estimated savings. This is why request-level routing is more interesting than simply assigning a different model to every task.

Anthara Fairooz

28,520 просмотров • 2 месяцев назад

Ran a real 3-turn LinkedIn research workflow through GMI Cloud Router in Balanced mode. Here’s what it actually picked, turn by turn : Turn 1 — “Research 2026 AI/marketing trends and summarize 5 insights” → DeepSeek-V4-Flash-0731 → ~$0.047 cheaper than Claude Opus 4.8 Turn 2 — “Analyze those insights for content angles + pain points” → GPT-5.6-Luna → ~$0.026 saved vs Opus 4.8 Turn 3 — “Turn the top angle into 5 LinkedIn post concepts” → GPT-5.6-Luna → ~$0.040 saved vs Opus 4.8 Total estimated savings: ~$0.11 across 3 turns. The interesting part was Turns 2 and 3. The task changed from analysis to writing, but Router stayed on GPT-5.6-Luna. That makes sense because GMI Router is cache-aware: when the same model can still handle the next task well, staying on that model can preserve cache reuse and avoid the cost of re-serving the context to another model. And all 3 tasks were relatively lightweight. They didn't suddenly require a more expensive frontier model just because the task type changed. So the routing wasn't about constantly switching models. It was about finding a model that was good enough for the task while keeping the cost down, and staying there when that still made sense. That’s a much more interesting way to think about model routing. GMI Cloud #AI #LLM #AIAgents #GenerativeAI

Ran a real 3-turn LinkedIn research workflow through GMI Cloud Router in Balanced mode. Here’s what it actually picked, turn by turn : Turn 1 — “Research 2026 AI/marketing trends and summarize 5 insights” → DeepSeek-V4-Flash-0731 → ~$0.047 cheaper than Claude Opus 4.8 Turn 2 — “Analyze those insights for content angles + pain points” → GPT-5.6-Luna → ~$0.026 saved vs Opus 4.8 Turn 3 — “Turn the top angle into 5 LinkedIn post concepts” → GPT-5.6-Luna → ~$0.040 saved vs Opus 4.8 Total estimated savings: ~$0.11 across 3 turns. The interesting part was Turns 2 and 3. The task changed from analysis to writing, but Router stayed on GPT-5.6-Luna. That makes sense because GMI Router is cache-aware: when the same model can still handle the next task well, staying on that model can preserve cache reuse and avoid the cost of re-serving the context to another model. And all 3 tasks were relatively lightweight. They didn't suddenly require a more expensive frontier model just because the task type changed. So the routing wasn't about constantly switching models. It was about finding a model that was good enough for the task while keeping the cost down, and staying there when that still made sense. That’s a much more interesting way to think about model routing. GMI Cloud #AI #LLM #AIAgents #GenerativeAI

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Introducing Cursor Router, our intelligent model router that selects the right model for the task at hand. Router delivers frontier-quality results at 60% lower cost.

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Gemini 3.8 Flash vs Opus 5 same prompt to each model and i wasn't expecting gemini 3.8 flash to be this fast! build time: > Opus 5: 24 minutes > 3.8 Flash: 37 seconds 💀 if gemini is given same time as opus 5 it will mog the hell out of opus in terms of quality too which one would you choose here?

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Tim Jayas

76,990 просмотров • 2 месяцев назад

We made Fable 5.1 compete against Entelligence Router on the same coding task. Both had the same harness and infra, and had to build a GeoGuessr-style game from scratch, implement the interactions, and verify everything in the browser. Fable 5.1: 21 min, $22.16 Entelligence Router: 21 min, $9 Fable delivered a strong result, although we did run into some overlay bugs along the way. Entelligence got the same task done at 59% lower cost.

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Aguilar: What is the estimated cost of the deployment for the National Guard and the Marines to LA? MacDonnell: The current estimated cost is $134 million

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DeepSeek V4.1 Flash 1017 vs Minimax M3.1 Flash Same prompt. Same task. Deepseek Time: 1 h 28 min 27 s Tokens: 89.487.454 Cost: $0,54 Minimax Time: 1 h 6 min 51 s Tokens: 8.120.000 Cost: $0,22 Which one is better?

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Agent Categories and Costs are now in the Agent Leaderboard! Two questions guide model selection: task-specific performance and cost to completion. Based on analysis of 1.7M+ real-world Agent Mode sessions, the leaderboard now lets users: - Filter the leaderboard by Code, Work, and Chat to compare model performance by task type - View real cost-per-task for each model, including the Pareto frontier of the most cost-efficient options at each performance level

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Gemini Flash 3.8 beats Opus 5 at at 15× lower price the test: four self-contained three.js physics scenes — a balloon popped by a needle, a ball dropping into water, a bomb with a mushroom cloud, a live atom model. 5 seconds each, real gravity, real impact. cost: Gemini 3.8 Flash — $0.12 Claude Opus 5 — $1.86 what we saw: • gemini passes the same physics checklist for 15× less — the ball sinks and bobs, ripples spread, the mushroom towers over the scene • gemini is 4× faster — every scene generated in under 70 seconds. opus took up to 5 minutes try Gemini 3.8 Flash on aimlapi[.]com

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Someone built a plugin that cuts Claude Code's cost by 54% on the same task, same model. Not a different model. Not a different harness. Just smarter tools underneath. It's called WOZCODE and the benchmark numbers are genuinely CRAZYYYY.

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I gave the exact same prompt to Qwen 3.7 Max and GLM 5.2. Same workflow. Same platform. Nearly the same starting price. The results weren't even close. Here's what happened. 👇

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Opus 5.5 vs Gemini 4 Argon Same prompt. Same task: build a cinematic 3D animation explaining how a Tesla-style electric motor works. Which one do you think did better?

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193,298 просмотров • 29 дней назад

DeepSeek-V4-Flash vs Gemini-3.6-Flash both given the exact same prompt to build 3D pirate ship Cost: > deepseek-v4-flash: $0.14 / $0.28 > gemini-3.6-flash: $1.50 / $7.50 though deepseek is 20x cheaper, gemini was surprising faster with the output Prompt used: "build a 3D model of pirate ship in Three js with minimal dashboard buttons in light theme background, with wide view of the pirate ship"

DeepSeek-V4-Flash vs Gemini-3.6-Flash both given the exact same prompt to build 3D pirate ship Cost: > deepseek-v4-flash: $0.14 / $0.28 > gemini-3.6-flash: $1.50 / $7.50 though deepseek is 20x cheaper, gemini was surprising faster with the output Prompt used: "build a 3D model of pirate ship in Three js with minimal dashboard buttons in light theme background, with wide view of the pirate ship"

Tim Jayas

20,127 просмотров • 3 месяцев назад

🚨 Gemini 4 Argon vs Opus 5.5 Same prompt Gemini 4 Argon has made a HUGE comeback it's directly Compating with opus 5.5 the quality seem the same I think Opus 5.5 feels little bit better but I didn’t expect Google to close the gap this much Google is COOKING

🚨 Gemini 4 Argon vs Opus 5.5 Same prompt Gemini 4 Argon has made a HUGE comeback it's directly Compating with opus 5.5 the quality seem the same I think Opus 5.5 feels little bit better but I didn’t expect Google to close the gap this much Google is COOKING

Salio

68,004 просмотров • 29 дней назад

WTH.. did Ox Alpha achieved self-learning, or what ?? I gave it the exact same prompt I used 3 days ago, but the output is completely different. For the same task, it took 330 mins instead of 80 mins and wrote 4,500+ lines of code. how 😬.....?

WTH.. did Ox Alpha achieved self-learning, or what ?? I gave it the exact same prompt I used 3 days ago, but the output is completely different. For the same task, it took 330 mins instead of 80 mins and wrote 4,500+ lines of code. how 😬.....?

Adit_Yah ☄️

12,130 просмотров • 2 месяцев назад

Gemini 4 Argon vs Claude Sonnet 5.5 vs Claude Opus 5.5 vs GPT-6 Astra The Lighthouse benchmark, all four frontier models side by side 🌊🔦 Same prompt. Same XHigh Effort • Gemini 4 Argon: $6.30, 1h 47m 35s • Claude Sonnet 5.5: $29.90, 2h 41m 44s • Claude Opus 5.5: $53.57, 2h 44m • GPT-6 Astra: $42.28, 2h 29m Honestly, Gemini 4 Argon blew me away again. 🤯 That glowing lantern and those turquoise waves for $6.30. That's 8x cheaper than Claude Opus 5.5! Next up: DeepSeek V4.1 Flash 1017 vs MiniMax M3.1 Flash on the same lighthouse. 🥊 What do you guys think? 👀

Gemini 4 Argon vs Claude Sonnet 5.5 vs Claude Opus 5.5 vs GPT-6 Astra The Lighthouse benchmark, all four frontier models side by side 🌊🔦 Same prompt. Same XHigh Effort • Gemini 4 Argon: $6.30, 1h 47m 35s • Claude Sonnet 5.5: $29.90, 2h 41m 44s • Claude Opus 5.5: $53.57, 2h 44m • GPT-6 Astra: $42.28, 2h 29m Honestly, Gemini 4 Argon blew me away again. 🤯 That glowing lantern and those turquoise waves for $6.30. That's 8x cheaper than Claude Opus 5.5! Next up: DeepSeek V4.1 Flash 1017 vs MiniMax M3.1 Flash on the same lighthouse. 🥊 What do you guys think? 👀

Tony

17,981 просмотров • 20 дней назад

Kimi K3 vs Fable 5. $0.45 vs $1.85. same prompt, same one-shot. the task: a cinematic 3D animation of an army helicopter flying through the Vietnam jungle during the war. both built it. K3 did it for a quarter of the cost. which one actually nailed it?

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Gemini 3.5 Flash vs Composer 2.5 Fast 🏁 Running the same task on the iOS simulator using Argent Gemini finished over 2x faster 🤯

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