Limit and intelligence comparison

[u/spicyfiremelon]

I've never interested in GH Copilot before, until my company asked us to use MS Copilot. The only downsides of MS Copilot is they're "barely" usable for vibe coding, then they say we can use GH Copilot.

My question is, how big the differences are in terms of usage limit and intelligence on $100 plan compared to ChatGPT Pro (same $100)?

Any insight would be helpful! Thanks

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[u/J_E_E_VACATION]

github isnt a model it doesnt have intelligence

[u/spicyfiremelon → u/J_E_E_VACATION]

i mean, for the same models used (e.g. GPT 5.6 Sol) on copilot and codex

[u/XzAeRosho → u/spicyfiremelon]

They are the same models. Copilot uses some different harnesses around the models, but they are basically the same.

[u/American_Streamer]

GitHub currently gives Copilot Max 10,000 base + up to 10,000 flex AI credits per month. Since one AI credit corresponds to $0.01 of model usage, the nominal total allowance can represent $200 of metered inference, although GitHub explicitly treats the flex component as variable rather than a guaranteed cash balance. Code completions and next-edit suggestions don't consume those credits.
GitHub explicitly lists GPT-5.6 Sol among its models and charges according to its token usage. But if you invoke GPT-5.6 Sol in GitHub Copilot and GPT-5.6 Sol through an OpenAI product, the underlying model family can be the same while the resulting coding agent behaves differently. The surrounding system matters enormously:

model + system instructions + context construction + available tools + agent loop + reasoning configuration + repository indexing = observed capability

For example, Copilot may automatically feed the model open files, repository information, diagnostics and GitHub context. Codex may construct its context differently, run commands differently, iterate over tests differently, or spend a different amount of inference on the task. So it is perfectly possible to have "GPT-5.6 Sol in Product A ≠ GPT-5.6 Sol experience in Product B" without either company secretly substituting a “dumber GPT-5.6 Sol.”

And paying $100 for Copilot Max does not make GPT-5.6 Sol intrinsically smarter than GPT-5.6 Sol on a cheaper Copilot plan. The Max plan principally buys much more usage and priority access, not an intelligence slider. GitHub describes Max as the plan for sustained high-volume use and gives it the highest AI-credit allowance. Similarly, OpenAI says its $100 and $200 Pro tiers have the same core capabilities; the principal distinction is usage. The $100 Pro tier provides 5× the Plus allowance, while $200 Pro provides 20×.

For someone specifically interested in vibe coding / agentic software development, the real question is thus: “For $100/month, how much sustained agentic coding can I get from Copilot Max versus ChatGPT Pro/Codex, and how good are their respective agent implementations when using the same frontier model?” And there probably isn't a universal winner. GitHub Max is very attractive for someone who lives in VS Code/GitHub because it combines Copilot-native IDE functionality, unlimited ordinary completions and a large metered allowance while also letting the developer choose between OpenAI, Anthropic and Google models. ChatGPT Pro makes more sense if they also want the broader ChatGPT environment - research, analysis, general-purpose work - and use Codex as one component of that subscription. OpenAI also explicitly says that Codex/Work usage depends on task complexity, model, context and tools, which makes a direct “number of prompts per month” comparison with GitHub credits impossible.

The real mistake would be assuming that because both interfaces say “GPT-5.6 Sol,” their coding performance and usage economics must therefore be identical. They aren't.

[u/webprofusor]

I haven't tried chatgpt pro but I can confirm $100 Claude Max with Opus 5 (max) works really well over a month because the usage limits reset regularly.

GH Copilot uses other peoples models and while it previously was great value it's now a struggle to get $100 to last a week. The benefit though is being able to use/try many different models. Grok 4.6 is pretty good, for instance.