terminal-bench 4.0 jumped from 31.2% to 42.3%.
but the old score used deepseek harness, while the new one used claude code.
deepseek harness actually beat claude code on terminal-bench 2.1 with the old model.
what does "optimized for deepseek harness" mean here?
🚀 DeepSeek-V4.1-Flash-1017 is here!
Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.
🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model.
1/4
this could be a blessing in disguise for builders.
as subscriptions approach API prices, you no longer have to compete with insane subsidies.
and you still keep the upper hand of being model and harness agnostic.
Hi,
Tomorrow we are re-opening the Pro $200 subscriptions to new subscribers, but together with it we are also changing how we calculate the usage for it. In effect, if you do the math, it will net out at half the dollar in API spend compared to the old Pro $200 plan.
Now that it's said, let me explain why this is happening and why you will still get more work done than if you were on the Pro $200 subscription one month ago.
(a) We didn't want to compromise in other ways and are committing to not reintroducing the 5h limit, so that you can fully use the weekly usage when you want.
(b) On the subscription, we guarantee that over time you always get more work done and with an increasing level of quality. This means that you will continue to get more value per dollar spent as a result of models getting more efficient and us passing down the improvements in the form of API price reductions.
(c) We don't want to put an incentive on ourselves to artificially inflate the API list prices to make it look like you are getting a lot (and workaround it through discounts, etc). Instead we want to continue to both rapidly reduce prices and increase capabilities of models on the API. This week we introduced GPT-6 Sol and GPT-6 Luna at 50% of their previous price. Over time, we see prices go low enough that it makes sense for most to buy usage as needed without there being a significant gap between what you get in a subscription and what you get in the API for a dollar spent.
(d) Tomorrow, we are adding more things to the subscription that won't draw on the usage, I won't reveal what that is yet.
I wanted to be transparent before all the big announcements tomorrow. Lots of new exciting things are coming to the subscriptions that will make it super compelling, but I wanted to make sure to share this change ahead of time so you can all understand it before we shower you with good news.
Codexingly,
Tibo
so much variance depending on the harness.
harness matters folks.
in 1817, beethoven was obsessed with fugues.
got 6 astra took one of his unfinished scribbles, turned it into a playable string quintet, and helped visualize how the music might have felt as his hearing faded.
beethoven’s NE 114 fugue sketch was the input. here's the code: github.com/andyrewlee/beetho…
this week i got following usage ($200 claude sub)
- 5.3B tokens (50/50 fable and opus)
- $4,300 API cost
this means starting 9/14 it would be
- 4.3B tokens
- $3,569 API cost
i regret to inform you, even after this reduction, it would be on par with codex outside of resets.
Replying to @ClaudeDevs
Compared to today, this works out to a 17% reduction in weekly limits on Claude Code. We’re working on exciting changes that will make it feel like you’re getting more from Claude, while having more visibility and control of your usage. Can’t wait to share them.
wow this model is fast and furious
prompt: bluey and bingo acting very shocked that openai is pulling their models from cursor
🤖 Made with AI
we're offering FREE MiniMax H3 Max generations on fal, both T2V and I2V! Try it out: fal.ai/tools/minimax-h3-max
so fast it can livestream xitter.cf/rehan_shei/status/2093…
relevant pr github.com/openai/codex/pull…
many agents is bad ux they said as we converged on single agent, multiple sessions with model picker.
what stands out most to me is grok bot adopts a different paradigm.
many agents, single session and no model picker. worth giving a shot to experience something new.
if you’re running out of codex usage, get high quality output for free by
1. writing plans with chatgpt pro
2. implementing with fx using glm 5.2
PSA: fx.sh has free GLM-5.2 for 2 weeks from @blackboxai, and 50% off @ChatGPT Sol for a month if you use ▲ AI Gateway. Sol is a brainiac, GLM-5.2 is a workhorse.
Usage is much higher than we anticipated. We're working on adding more GLM capacity!
Ox Alpha is also free on opencode. better free option than fx since it’s smarter than GLM 5.2 and there’s less throttling. xitter.cf/opencode/status/209054…
i’m getting addicted to gemini 3.7 flash.
it’s roughly on par with sonnet 5 and gpt terra but ~5x faster.
no other model this smart is this fast.
🚨 Google’s Gemini 3.7 Flash unexpectedly pulled off a pretty wild benchmark result.
On Artificial Analysis’ AA-AnalystAgent benchmark, it scored 60.0%, taking the #1 spot ahead of:
• Claude Opus 5: 53.8%
• GPT-5.5: 50.0%
• Claude Fable 5: 48.8%
• GPT-5.6 Sol: 47.5%
• Grok 4.6: 41.3%
That’s a Flash-tier model outperforming several flagship frontier models, Google AI might not be as far behind as we think.
“scaling post-training is all we did for GLM 5.3”
Introducing GLM-5.3: Built to Code. Ready for Cyber Defense.
- Top-tier coding and agentic capabilities, achieved through post-training on the 743B base model
- A major leap in cybersecurity, setting a new standard among open models
Tech Blog: z.ai/blog/glm-5.3
"plugin" will become the word that bridges the end user and the developer.
even if anthropic doesn't join this open standard, they already have plugins.
MCP, CLI, API and skills are just implementation details.
Build a plugin once and use it across compatible agent clients.
Introducing Agent Plugins, an open standard developed with @awsdevelopers, @cursor_ai, @github, @code, and @vercel that packages Agent Skills and supports MCP server configurations in a shared format.
i’m building with the following assumptions
1. most inference will run on open weight models
2. the harness will matter more than the model
3. most agents will live in the cloud
4. every app will become agent native
5. companies will spend more on agents than on people



















