All tags
Topic: "model-deprecation"
not much happened today
gpt-5 gpt-4o grok-4 claude-4-sonnet openai microsoft reasoning latency model-routing benchmarking reinforcement-learning hallucination-control creative-writing priority-processing api-traffic model-deprecation user-experience model-selection voice-mode documentation sama nickaturley elaineyale6 scaling01 mustafasuleyman kevinweil omarsar0 jeremyphoward juberti epochairesearch lechmazur gdb
OpenAI launched GPT-5 with a unified user experience removing manual model selection, causing initial routing and access issues for Plus users that are being addressed with fixes including restored model options and increased usage limits. GPT-5 introduces "Priority Processing" for lower latency at higher price tiers, achieving ~750ms median time-to-first-token in some cases. Microsoft reports full Copilot adoption of GPT-5, and API traffic doubled within 24 hours, peaking at 2 billion tokens per minute. Early benchmarks show GPT-5 leading in reasoning tasks like FrontierMath and LiveBench, with improvements in hallucination control and creative writing, though some models like Grok-4 and Claude-4 Sonnet Thinking outperform it in specific RL-heavy reasoning benchmarks. OpenAI also released extensive migration and feature guides but faced some rollout issues including a broken code sample and a problematic Voice Mode launch. "Unified GPT-5" ends model pickers, pushing developers away from manual model selection.
SOTA Video Gen: Veo 2 and Kling 2 are GA for developers
veo-2 gemini gpt-4.1 gpt-4o gpt-4.5-preview gpt-4.1-mini gpt-4.1-nano google openai video-generation api coding instruction-following context-window performance benchmarks model-deprecation kevinweil stevenheidel aidan_clark_
Google's Veo 2 video generation model is now available in the Gemini API with a cost of 35 cents per second of generated video, marking a significant step in accessible video generation. Meanwhile, China's Kling 2 model launched with pricing around $2 for a 10-second clip and a minimum subscription of $700 per month for 3 months, generating excitement despite some skill challenges. OpenAI announced the GPT-4.1 family release, including GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano, highlighting improvements in coding, instruction following, and a 1 million token context window. The GPT-4.1 models are 26% cheaper than GPT-4o and will replace the GPT-4.5 Preview API version by July 14. Performance benchmarks show GPT-4.1 achieving 54-55% on SWE-bench verified and a 60% improvement over GPT-4o in some internal tests, though some critiques note it underperforms compared to other models like OpenRouter and DeepSeekV3 in coding tasks. The release is API-only, with a prompting guide provided for developers.
GPT 4.1: The New OpenAI Workhorse
gpt-4.1 gpt-4.1-mini gpt-4.1-nano gpt-4o gemini-2.5-pro openai llama-index perplexity-ai google-deepmind coding instruction-following long-context benchmarks model-pricing model-integration model-deprecation sama kevinweil omarsar0 aidan_mclau danhendrycks polynoamial scaling01 aravsrinivas lmarena_ai
OpenAI released GPT-4.1, including GPT-4.1 mini and GPT-4.1 nano, highlighting improvements in coding, instruction following, and handling long contexts up to 1 million tokens. The model achieves a 54 score on SWE-bench verified and shows a 60% improvement over GPT-4o on internal benchmarks. Pricing for GPT-4.1 nano is notably low at $0.10/1M input and $0.40/1M output. GPT-4.5 Preview is being deprecated in favor of GPT-4.1. Integration support includes Llama Index with day 0 support. Some negative feedback was noted for GPT-4.1 nano. Additionally, Perplexity's Sonar API ties with Gemini-2.5 Pro for the top spot in the LM Search Arena leaderboard. New benchmarks like MRCR and GraphWalks were introduced alongside updated prompting guides and cookbooks.
Mistral Large 2 + RIP Mistral 7B, 8x7B, 8x22B
mistral-large-2 mistral-nemo-12b llama-3.1-8b llama-3.1-70b llama-3.1 llama-3-405b yi-34b-200k gpt-4o mistral-ai meta-ai-fair groq togethercompute code-generation math function-calling reasoning context-windows model-deprecation pretraining posttraining benchmarking
Mistral Large 2 introduces 123B parameters with Open Weights under a Research License, focusing on code generation, math performance, and a massive 128k context window, improving over Mistral Large 1's 32k context. It claims better function calling capabilities than GPT-4o and enhanced reasoning. Meanwhile, Meta officially released Llama-3.1 models including Llama-3.1-70B and Llama-3.1-8B with detailed pre-training and post-training insights. The Llama-3.1 8B model's 128k context performance was found underwhelming compared to Mistral Nemo and Yi 34B 200K. Mistral is deprecating older Apache open-source models, focusing on Large 2 and Mistral Nemo 12B. The news also highlights community discussions and benchmarking comparisons.