Discussion

• @sama Sam Altman on x

  GPT-5.3-Codex-Spark is launching today as a research preview for Pro. More than 1000 tokens per second! There are limitations at launch; we will rapidly improve.

• @openai @openai on x

  Rolling out today to ChatGPT Pro users in the Codex app, CLI, and IDE extension. https://openai.com/...

• @openai @openai on x

  GPT-5.3-Codex-Spark is now in research preview. You can just build things—faster. [video]

• @danshipper Dan Shipper on x

  BREAKING: @OpenAI just launched a new Codex model, Spark—it serves at 1,000 tokens per second. It's blow your hair back fast. It's their first model publicly released on Cerebras hardware, and you can see the difference. We've been testing internally @every for the last week or

• r/singularity r on reddit

  Introducing GPT-5.3-Codex-Spark.  An ultra-fast model for real-time coding in Codex

• @openaidevs @openaidevs on x

  GPT-5.3-Codex-Spark is the first milestone in our partnership with @cerebras. It provides a faster tier on the same production stack as our other models, complementing GPUs for workloads where low latency is critical. https://openai.com/...

• @openaidevs @openaidevs on x

  Introducing GPT-5.3-Codex-Spark, our ultra-fast model purpose built for real-time coding. We're rolling it out as a research preview for ChatGPT Pro users in the Codex app, Codex CLI, and IDE extension. [video]

• @scaling01 @scaling01 on x

  GPT-5.3-Codex-Spark size: ~700B@30B OpenAI's new GPT-5.3-Codex-Spark is the first model for which we can somewhat reliably estimate its size. Cerebras inference: 1000 tokens/s - GLM-4.7 is 355@32B, 92 layers 1400 tokens/s - Qwen3-235B is 235@22B, 94 layers 3000 tokens/s - [image]

• @eliebakouch Elie on x

  ok this is very interesting, this is not the same perf than gpt5.3, and might not be the same arch as well? > Codex-Spark marks the first milestone in our partnership with Cerebras. Codex-Spark is optimized to feel near-instant when served on ultra-low latency hardware (from [ima…

• @kevinweil Kevin Weil on x

  Coding at 1000 tokens/sec is a mind-expanding experience. You have to try this.

• @skirano Pietro Schirano on x

  Been using this model for a bit now, the combination of speed and intelligence is insane. It genuinely feels like a new paradigm shift. Excited to plug it into more specialized coding pipelines.

• @romainhuet Romain Huet on x

  Hello GPT-5.3-Codex-Spark! ✨ Our first real-time coding model. It is... FAST. 1,000+ tokens per second. Once you experience latency this low, it's hard to go back. This is an exciting first milestone in our partnership with @Cerebras. [video]

• @heccbrent Brent Schooley on x

  This was so fun to work on. GPT-5.3-Codex-Spark built a snake game so fast that I was able to start setting high scores in about 9 seconds. If you have ChatGPT Pro you're going to want to check this out today! [video]

• @_simonsmith Simon Smith on x

  We've seen how much speed affects people's model preferences recently (e.g. the arena @swyx is running), so I think Codex Spark will be well-received. Also interesting that this initial release is a step towards combining long-horizon and real-time agents, including delegating to…

• @embirico Alexander Embiricos on x

  ✨GPT-5.3-Codex-Spark✨ We're rolling out our first @cerebras model to Pro users today. It's fast! Rollout will be slow and very capacity constrained. Excited to roll out to more folks, and improve it with your feedback.

• @derrickcchoi Derrick Choi on x

  One of the top pieces of feedback we get about @OpenAI Codex: “make it faster”. We addressed it in a big way with our ultra fast Codex-Spark model (research preview for Pro). Available in the latest Codex app, CLI, and IDE extension. Here's Spark vs 5.3-Codex-Low side-by-side [vi…

• @mweinbach Max Weinbach on x

  GPT 5.3 Codex Spark! It's a smaller version of GPT 5.3 Codex running at over 1000 tokens per second on Cerebras hardware GPT 5.3 Codex was trained for GB200, on GB200. I wonder what this is? Maybe GPT 5.3 Codex that used Cerebras Reap?

• @dimillian Thomas Ricouard on x

  I've been playing with GPT-5.3-Codex-Spark this week, and it's a really a✨ experience. Basically, using it for smaller tasks, context scanning, quick analysis, and smaller code edits. It feels so natural and instant; it's really hard to go back to other models.

• @kylebrussell Kyle Russell on x

  I thought this was going to come like next year, not now

• @benbajarin Ben Bajarin on x

  As the world moves to inference, dedicated inference designs will be prominant. Great customer case for @cerebras

• @cerebras @cerebras on x

  OpenAI Codex-Spark powered by Cerebras You can now just build things faster—at 1,000 tokens/s. [video]

• @mweinbach Max Weinbach on x

  Codex Spark was trained on GPUs for Cerebras hardware but OpenAI added support to their inference framework for Cerebras meaning they're reading to load future models onto it too GPUs are still foundational for inference and training, though [image]

• r/OpenAI r on reddit

  Introducing GPT-5.3-Codex-Spark

• @sungkim Sung Kim on bluesky

  OpenAI has released GPT-5.3-Codex-Spark: 1000 tokens per second  —  openai.com/index/introd...  [embedded post]

• @andrewdfeldman Andrew Feldman on x

  Just one month after announcing our partnership with @OpenAI, we're launching our first model together: OpenAI Codex-Spark, powered by @cerebras. Codex-Spark is built for real-time software development. In coding, responsiveness is the product. It is not a nice to have. [image]