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[ARTICLE · art-77654] src=peterbe.com ↗ pub= topic=large-language-models verified=true sentiment=↓ negative

Claude Opus is 10x faster than OpenAI GPT 5 at non-streaming completions

An independent developer reports that Anthropic's Claude Opus 4.8 is nearly 10 times faster than OpenAI's GPT-5 at non-streaming completions, based on side-by-side testing of blog comment rewrites. The developer also found that OpenAI's GPT-5-mini is both cheaper and faster than GPT-5, with input token pricing at $0.75 versus $2.50 for GPT-5.4, and is moving away from the litellm wrapper to use native SDKs from Anthropic and OpenAI due to security concerns.

read2 min views13 publishedJul 24, 2026
Claude Opus is 10x faster than OpenAI GPT 5 at non-streaming completions
Image: Peterbe (auto-discovered)

This picture summarizes it well:

Here on my blog, for this popular blog post I get a lot of comments. 28k blog comments over the years. Some of them are terribly written and hard to understand, so I let AI suggest a rewrite. That code that sends the blog post comment to AI, I actually fire off three times: once with OpenAI gpt-5

, once with OpenAI gpt-5-mini

, and once with Claude claude-opus-4.8

. I use my human eyes and judgement to evaluate the results, and I can tell you they do equally well. Only the slightest differences.

The surprising thing is how amazingly slow OpenAI's gpt-5

is! It's nearly 10x slower than claude-opus-4.8

. What's up with that!?

It's also clear that the latency difference between gpt-5-mini

and gpt-5

is significant. At the time of writing, the input token price difference between gpt-5.4

and gpt-5.4-mini

is $2.50 compared to $0.75! That's a 3x difference.

Conclusion

If you're constructing a prompt the API, use Claude.

If you have to use OpenAI, consider the

mini

model because it'sbothcheaperandfaster.

Bonus

Before I added Claude, I used to use litellm

to wrap OpenAI's models. The code looks like this:

response = litellm.completion(
    model="openai-gpt-5",
    api_key=settings.OPENAI_API_KEY,
    messages=my_prompt_messages,
)

Unlike, if you use the native OpenAI Python SDK the invocation looks like this:

client = openai.OpenAI(api_key=settings.OPENAI_API_KEY)
response = client.responses.create(
    model="gpt-5,
    input=my_prompt_messages,
)

I measured the difference, in speed, where I compare using the OpenAI SDK versus the litellm

wrapper and the difference looks like this:

Granted, in June I "only" did a bit over 30 of these calls, but strangely there's a difference!

I don't have the intricate knowledge to understand why the litellm

makes the total time different from using the SDK. (not sure I care either!)

Either way, I'm moving away from litellm

and only use the SDKs provided by Claude and OpenAI. Feels safer given the CVEs we've seen this year on litellm

.

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