Rendered at 08:12:15 GMT+0000 (Coordinated Universal Time) with Cloudflare Workers.
tekacs 2 hours ago [-]
I'm pretty baffled by their choice of axes. I would have thought that the left was the cheapest, not the most expensive. I appreciate that this layout means that top right can be best, but it's still unintuitive to have this backwards cost axis IMO.
Putting that aside, I spend all day every day implementing very, very hard things right on the edge of what agents are (barely, sometimes) capable of, and I have had to keep Opus on max for things that need 'real validation' for a while now. And that has felt like 'the only way' to get Opus to perform even close to 5.5 xhigh. I'm only using Opus at all because GPT-5.5 in the subscriptions only has a small (400k, but 258k effective) context window.
The difference is that 5.5 xhigh is extremely fast in most practical cases, both efficiently implementing _overall_, and responding very quickly with great adaptive thinking if you ask it something that it doesn't have to think about. Opus 4.8 Max will needlessly chew on everything and can take hours to implement even simple things, so I can mostly only use it for planning/review.
Fable is much much better at adaptive thinking / responding quickly (although probably still worse than 5.5 xhigh), and... I think folks have said enough elsewhere about its strengths and weaknesses. Sadly still not a reliable implementor for my hard tasks though (that's still GPT's domain) – it tends to leave big, dangerous holes hiding inside implementations unless babied.
cherryteastain 11 minutes ago [-]
You can set GPT 5.5 to 1M context mode in Cursor but it costs more after the default 272k.
pbowyer 1 hours ago [-]
> I'm only using Opus at all because GPT-5.5 in the subscriptions only has a small (400k, but 258k effective) context window.
Do you find that makes a difference in your work? I've been using 5.5 high/xhigh to optimize and benchmark a C codebase, and just reading the initial code virtually fills the first context window. A session will auto-compact 5-15 times, but it seems to do okay in spite of that because the task is mainly focused on the latest window each time.
I think for programming the strength of GPT over Opus is winning here over the context window.
mdasen 1 hours ago [-]
I'm a bit skeptical.
Cursor's benchmark finds that Cursor's model (Composer 2.5) is basically as good as Opus 4.8 max and GPT-5.5 xhigh, but at a fraction of the price.
Artificial Analysis' testing shows Composer 2.5 to be pretty far behind: https://artificialanalysis.ai/agents/coding-agents. You look at the DeepSWE benchmark (which is probably the hardest to game at this point) and GPT-5.5 xhigh gets a 64, Opus 4.8 max gets 56, and Cursor 2.5 gets 16.
I don't doubt that Cursor works well for some people. It's beating DeepSeek v4 Pro in the DeepSWE benchmark and that's a very capable model. But I'm skeptical of the claims that it's a competitor for Opus 4.8 and GPT-5.5. It just seems convenient that their model does so well on their own benchmark while third party benchmarks have it far behind. Maybe it's a really great benchmark and a better measure than third party ones - I'd love for a cheap model to do as well as the expensive ones.
ciaf 2 minutes ago [-]
By the same token, Fable 5 is given a score of 77 vs 76 for GPT 5.5
datadrivenangel 39 minutes ago [-]
For lighter interactive agentic coding, where you type stuff into an IDE and a minute or three later get results back for review, composer 2.5 is honestly pretty great. The results get notably worse for larger tasks though.
famouswaffles 1 hours ago [-]
Cursor sessions are pretty much what composer models are RL'd on. This bench and the training data are/should be basically the same distribution.
__natty__ 34 minutes ago [-]
It's hard to believe Composer 2.5 is that good. I tried to compare it with GLM 5.2 or Opus 4.6 and it lacked thinking about the problem and critical reasoning. It's great for executing plans made by other models, but even then it does some weird code manipulation that is far from how other files around actually work.
verse 18 minutes ago [-]
backwards X axis? is there a reason for that? it looks ridiculous
gkbrk 16 minutes ago [-]
It looks very natural, cheaper is better after all. Performance axis going up, and cheapness axis going up match each other.
anon373839 16 minutes ago [-]
This seems to be a common choice with AI industry graphs, to give you that “upward and outward” frontier shape.
BugsJustFindMe 55 minutes ago [-]
I've used both Composer 2.5 and GPT 5.5 (both in Cursor and in Codex) extensively, and their claim that Composer 2.5 is anywhere close in performance to GPT 5.5 is absolutely farcical. It's faster, but it's nowhere near as good.
And given that you can only use Composer with a Cursor monthly subscription, cost comparisons are pointless since an equivalently priced OpenAI subscription gets you just as much usage of the better model.
luckilydiscrete 14 minutes ago [-]
insert obama medal meme
o10449366 2 hours ago [-]
I feel like this benchmark reiterates my disbelief that anyone uses the latest Anthropic models for any productive work. They seem to be the best at burning tokens and spawning unnecessary subagents even for well-defined and tightly scoped tasks.
Can we get a count of people that have had Claude read irrelevant documents or perform unnecessary web searches even when told not to from the beginning?
I'm starting to wonder if this increased token usage is inadvertently bleeding into how Anthropic actually trains their model, especially leading up to IPO. As older models are deprecated and users are forced onto newer models, if the default is less efficient and more token expensive that directly results in higher "profit" for Anthropic in terms of the consumption their users have to tolerate - lest they jump to a competitor.
anon373839 8 minutes ago [-]
> I'm starting to wonder if this increased token usage is inadvertently bleeding into how Anthropic actually trains their model
> I feel like this benchmark reiterates my disbelief that anyone uses the latest Anthropic models for any productive work. They seem to be the best at burning tokens and spawning unnecessary subagents even for well-defined and tightly scoped tasks.
I keep Claude around for some specific tasks:
- Linked up to Figma MCP to implement front-end stuff
- Data analysis, in the "Connect AI to a data source and ask questions" way. I've tried both Opus 4.8 high and GPT 5.5 high for this and Opus is stronger because it gets the intent in the question better
I used to keep it around for planning too, but the 4.8 plans have had more holes than swiss cheese.
anilgulecha 2 hours ago [-]
is composer 2.5 that good at that pricepoint? Seems like the gemini flash playbook of trying to get most bang for the buck.
danfritz 2 hours ago [-]
It's my daily driver, it's fast affordable and with a bit of guidance gets the job done.
I only reach for Claud when i need to plan something big or want to have a sparring partner to fire of some ideas.
I think what a lot of people don't realize is that you don't need a fronteer model for 80% of coding tasks. Composer 2.5 is often more than good enough, less token hungry and way faster
shockembopper 1 hours ago [-]
I have been doing the same for quite a while now. Composer 2.5 is incredible when you’re working in the loop.
uf00lme 2 hours ago [-]
It's surprising usable and cheap enough to run in 'fast' mode when vibing something quick. For simple code I find I prefer the code it writes over GLM or Gemini family.
Putting that aside, I spend all day every day implementing very, very hard things right on the edge of what agents are (barely, sometimes) capable of, and I have had to keep Opus on max for things that need 'real validation' for a while now. And that has felt like 'the only way' to get Opus to perform even close to 5.5 xhigh. I'm only using Opus at all because GPT-5.5 in the subscriptions only has a small (400k, but 258k effective) context window.
The difference is that 5.5 xhigh is extremely fast in most practical cases, both efficiently implementing _overall_, and responding very quickly with great adaptive thinking if you ask it something that it doesn't have to think about. Opus 4.8 Max will needlessly chew on everything and can take hours to implement even simple things, so I can mostly only use it for planning/review.
Fable is much much better at adaptive thinking / responding quickly (although probably still worse than 5.5 xhigh), and... I think folks have said enough elsewhere about its strengths and weaknesses. Sadly still not a reliable implementor for my hard tasks though (that's still GPT's domain) – it tends to leave big, dangerous holes hiding inside implementations unless babied.
Do you find that makes a difference in your work? I've been using 5.5 high/xhigh to optimize and benchmark a C codebase, and just reading the initial code virtually fills the first context window. A session will auto-compact 5-15 times, but it seems to do okay in spite of that because the task is mainly focused on the latest window each time.
I think for programming the strength of GPT over Opus is winning here over the context window.
Cursor's benchmark finds that Cursor's model (Composer 2.5) is basically as good as Opus 4.8 max and GPT-5.5 xhigh, but at a fraction of the price.
Artificial Analysis' testing shows Composer 2.5 to be pretty far behind: https://artificialanalysis.ai/agents/coding-agents. You look at the DeepSWE benchmark (which is probably the hardest to game at this point) and GPT-5.5 xhigh gets a 64, Opus 4.8 max gets 56, and Cursor 2.5 gets 16.
I don't doubt that Cursor works well for some people. It's beating DeepSeek v4 Pro in the DeepSWE benchmark and that's a very capable model. But I'm skeptical of the claims that it's a competitor for Opus 4.8 and GPT-5.5. It just seems convenient that their model does so well on their own benchmark while third party benchmarks have it far behind. Maybe it's a really great benchmark and a better measure than third party ones - I'd love for a cheap model to do as well as the expensive ones.
And given that you can only use Composer with a Cursor monthly subscription, cost comparisons are pointless since an equivalently priced OpenAI subscription gets you just as much usage of the better model.
Can we get a count of people that have had Claude read irrelevant documents or perform unnecessary web searches even when told not to from the beginning?
I'm starting to wonder if this increased token usage is inadvertently bleeding into how Anthropic actually trains their model, especially leading up to IPO. As older models are deprecated and users are forced onto newer models, if the default is less efficient and more token expensive that directly results in higher "profit" for Anthropic in terms of the consumption their users have to tolerate - lest they jump to a competitor.
Related: Sonnet 5’s new tokenizer increases token usage by 30%. (https://simonwillison.net/2026/Jun/30/claude-sonnet-5/)
I keep Claude around for some specific tasks:
- Linked up to Figma MCP to implement front-end stuff
- Data analysis, in the "Connect AI to a data source and ask questions" way. I've tried both Opus 4.8 high and GPT 5.5 high for this and Opus is stronger because it gets the intent in the question better
I used to keep it around for planning too, but the 4.8 plans have had more holes than swiss cheese.
I only reach for Claud when i need to plan something big or want to have a sparring partner to fire of some ideas.
I think what a lot of people don't realize is that you don't need a fronteer model for 80% of coding tasks. Composer 2.5 is often more than good enough, less token hungry and way faster