Hasaan ch🇵🇰🇵🇸

Follow me. I will follow you Back!

Viva España 🇪🇸

@bridgemindai What will be its context window?

Kimi K3 is expected to drop TODAY. Kimi K2.7 Code is a joke of a model. I said it when it shipped and nothing changed my mind. But K3 is a different animal. The rumors say that Kimi K3 is a much larger model, on par with Claude Opus 4.7. If that is even half true, the open frontier just moved again. Remember what GLM 5.2 did to the leaderboard. High hopes. Zero benefit of the doubt. BridgeBench is waiting.

@jun_song Gemini 3.5 pro = Only good at benchmarks 😂

Upcoming models performance predictions : Opus-5 = Slightly worse than Fable, similar to GPT-5.6 Kimi-K3 = Very fast, slightly worse than Fable (tested) Deepseek-V4 = Opus-4.8 GLM-5.5 = Fable MiniMax-M3 Pro = Slightly worse than Fable Gemini-3.5-Pro = Only good at benchmarks

@Woundedlion__ Why they are showing some ugly stuff on screen?

Paki inbred. This is how it looks to fly in Air India business class ✨, don’t lie or Allah will starve Palestine kids

We're extending Claude Fable 5 access on all paid plans, as well as keeping Claude Code’s weekly rate limits 50% higher, through July 19.

When you realize life was better when:

@photon010 Wealth inequality

what should i name them??

Snake wasn’t aware of this 🐠

Gemini 3.5 has been delayed till the end of the month The goal is to catch up with Fable The problem is that Fable 5.1 and GPT 6 are supposed to launch in the same time frame

@thekennwakanma @bindureddy i tried grok for frontend. yeah its pretty good

@bindureddy How good is Grok 4.5 at front end?

People are shocked by how the PR of Argentina and Messi has fallen within days Social media has been filled with memes and posts against them

Muse Spark 1.1 outperforms Opus 4.8 and Grok 4.5 on some nice out of distribution evals :)

Good job! AUSTRALIA 🇦🇺

عاصم منیر کے اپنے پانچ بچے ہیں

@DilKNawabR @stats_feed Oh fuck off, people in pakistan don't have money to buy eggs, beef ,mutton. Everyone here consumes carbs , carbs, and carbs.

@stats_feed Indian Eating one time in a day just dal chawal roti achaar Pakistani eating 4 Time in a day Just like chicken Beef Mutton eggs fish and Night unlimited snks

Obesity rate 🇵🇰 Pakistan: 23.69% 🇮🇳 India: 7.51% 🇧🇩 Bangladesh: 5.41% Worldobesity, BMI > 30kg/m², adults

BREAKING: Benjamin Netanyahu reveals he's rooting for Argentina to win the 2026 World Cup.

GPT-5.6 Sol comes close second to Claude Fable 5 in the Artificial Analysis Intelligence Index at one third of the cost, and leads the Artificial Analysis Coding Agent Index in OpenAI’s Codex harness We supported @OpenAI with pre-release evaluation of GPT-5.6 Sol, Terra, and Luna. GPT-5.6 Sol (max) scores 1 point below Claude Fable 5 (max) in the Artificial Analysis Intelligence Index at 59 points, at approximately one third of the cost. GPT-5.6 Terra (max) and Luna (max) score 55 and 51 respectively in the Intelligence Index, at ~50% and ~80% lower Cost per Task than Sol. GPT-5.6 Sol (max) leads the Artificial Analysis Coding Agent Index at 80 points. Congratulations @OpenAI and @sama on the launch! Key takeaways: ➤ One third of the cost of Claude Fable 5: On max reasoning effort, GPT-5.6 Sol costs $1.04 per task in the Artificial Analysis Intelligence Index - offering a similar level of intelligence to Claude Fable 5 at approximately one third of the cost. Reasoning levels across GPT-5.6 Sol and Luna offer a range of options at the Pareto frontier of Intelligence vs Cost per Task. For example, GPT-5.6 Luna (max) matches or exceeds the intelligence of GLM-5.2 (max) and Gemini 3.5 Flash at a lower cost. GPT-5.6 Terra (max) and Luna (max) cost $0.55 and $0.21 per Intelligence Index task, ~50% and ~80% less than Sol. Across reasoning efforts, each new GPT-5.6 model pushes past GPT-5.5 on the Pareto frontier (excluding non-reasoning). Notably, Luna and Sol are always on the Pareto frontier ahead of Terra. This means that for any Terra effort level, there is a Luna or Sol effort level that is more intelligent at no extra cost, or as intelligent at lower cost. ➤ Leading in all Coding Agent evaluations: The new Artificial Analysis Coding Agent Index pairs models with agentic harnesses and features three frontier coding evaluations - DeepSWE, Terminal-Bench v2, and SWE-Atlas-QnA. GPT-5.6 Sol (max) in Codex scores 80 in the Index, leading in all three evaluations (tying Grok 4.5 in Grok Build for SWE-Atlas-QnA). In addition to scoring higher, its per task cost is ~40% and ~10% cheaper than Claude Fable 5 (max) and Opus 4.8 (max) respectively in Claude Code. GPT-5.6 Terra (max) and Luna (max) score 77 and 75 in the Coding Agent Index respectively, with ~60% and ~80% per-task cost reductions compared to Sol. ➤ Highest Presentation Elo in AA-Briefcase: GPT-5.6 Sol (max) ranks second only to Claude Fable 5 (max) in AA-Briefcase, and has the highest Presentation Elo of any model. AA-Briefcase is a new benchmark for testing models on realistic knowledge work tasks in complex projects built by industry experts. GPT-5.6 Sol (max) has the highest recorded Presentation Elo - its outputs across various file types, including PowerPoint and Excel, are the most visually attractive of any model. Fable 5 (max) still leads AA-Briefcase, largely due to its Rubric Score of 56% vs 42% for GPT-5.6 Sol (max). Fable 5 (max) also scores 1764 in Analytical Quality Elo vs GPT-5.6 Sol (max) at 1592. ➤ First OpenAI models with cache-write pricing: GPT-5.6 introduces cache-write pricing for the first time at OpenAI. Sol, Terra, and Luna are priced at $5/$30, $2.5/$15, and $1/$6 respectively per million input/output tokens. OpenAI has retained its previous discount of 90% for cache reads, but joins Anthropic in introducing a cost premium for cache writes, at 1.25x the price of input tokens. Cache writes occur when input tokens are committed to memory. Charging for a cache write more accurately reflects the model’s cost to serve, as cached tokens occupy memory whether or not they are reused. Also in line with Anthropic's models, GPT-5.6 introduces a max reasoning effort level. ➤ Low token use: GPT-5.6 Sol (max) uses fewer output tokens than most models of comparable intelligence, and defines a new Pareto frontier of Intelligence vs Output Tokens per Task. GPT-5.6 Sol (max) offers a slight improvement in token efficiency with 15k tokens per Intelligence Index task, vs GPT-5.5 at 16k. Notably, it uses fewer tokens and is more intelligent than Claude Opus 4.8 (max), GLM-5.2 (max), and Gemini 3.5 Flash (high).

@Seraphinaf5 71?