Claude 4.7 Opus vs Claude 4.5 Haiku

As you can see in the graph above, while in October, the use of Claude Sonnet 4.5 Thinking was normal, since the 1st of November, Perplexity has deliberately rerouted most if not ALL Sonnet 4.5 and 4.5 Thinking messages to far worse quality models like Gemini 2 Flash and, interestingly, Claude 4.5 Haiku Thinking which are probably cheaper models.

Perplexity is essentially SCAMMING subscribers by marketing their model as "Sonnet 4.5 Thinking" but then having all prompts given by a different model--still a Claude one so we don't realise!

Very scummy.

Anthropic just dropped Haiku 4.5 and the numbers are wild:

**Performance:**

* 73.3% on SWE-bench Verified (matches Sonnet 4 from 5 months ago)
* 90% of Sonnet 4.5's agentic coding performance
* 2x faster than Sonnet 4
* 4-5x faster than Sonnet 4.5

**Pricing:**

* $1 input / $5 output per million tokens
* That's 66% cheaper than Sonnet 4 ($3/$15)
* \~10x cheaper than Sonnet 4.5 for 90% of the performance

**Why this matters:**

Multi-agent systems are now economically viable. Before Haiku 4.5:

* 10 agents × $15/million = $150/million (too expensive)
* 10 agents × 10s latency = 100s total (too slow)

With Haiku 4.5:

* 10 agents × $5/million = $50/million (3x cheaper)
* 10 agents × 2s latency = 20s total (5x faster)

**Use cases unlocked:**

* Real-time chat assistants (2s response time)
* Automated code reviews (\~$0.01 per review)
* Pair programming with Claude Code (no latency friction)
* Rapid prototyping (iterate as much as you want)

**Available now:**

* Claude.ai
* Claude Code (CLI + extension) - use `/model` command
* API: `model="claude-haiku-4.5-20251015"`
* AWS Bedrock
* Google Cloud Vertex AI

We wrote a deep-dive article (in French, but code examples and benchmarks are universal) with cost analysis, migration guides, and real scenarios: [here](https://cc-france.org/blog/claude-haiku-45-le-modle-qui-redfinit-le-rapport-p)

The barrier between "proof of concept" and "production" just got dramatically lower.

What are you planning to build with it?

Press CTRL+I to invoke Windsurf Command ([documentation)](https://docs.windsurf.com/command/windsurf-overview): this generates code at your cursor, or it edits blocks of text. It never uses any credits.

Also, GPT 5.1 Codex and 5.1 Codex Mini are free in Cascade / chat ([documentation](https://docs.windsurf.com/windsurf/models)).

Anthropic just dropped Haiku 4.5 and the numbers are wild:

**Performance:**

* 73.3% on SWE-bench Verified (matches Sonnet 4 from 5 months ago)
* 90% of Sonnet 4.5's agentic coding performance
* 2x faster than Sonnet 4
* 4-5x faster than Sonnet 4.5

**Pricing:**

* $1 input / $5 output per million tokens
* That's 66% cheaper than Sonnet 4 ($3/$15)
* \~10x cheaper than Sonnet 4.5 for 90% of the performance

**Why this matters:**

Multi-agent systems are now economically viable. Before Haiku 4.5:

* 10 agents × $15/million = $150/million (too expensive)
* 10 agents × 10s latency = 100s total (too slow)

With Haiku 4.5:

* 10 agents × $5/million = $50/million (3x cheaper)
* 10 agents × 2s latency = 20s total (5x faster)

**Use cases unlocked:**

* Real-time chat assistants (2s response time)
* Automated code reviews (\~$0.01 per review)
* Pair programming with Claude Code (no latency friction)
* Rapid prototyping (iterate as much as you want)

**Available now:**

* [Claude.ai](http://Claude.ai)
* Claude Code (CLI + extension) - use `/model` command
* API: `model="claude-haiku-4.5-20251015"`
* AWS Bedrock
* Google Cloud Vertex AI

We wrote a deep-dive article (in French, but code examples and benchmarks are universal) with cost analysis, migration guides, and real scenarios: [here](https://cc-france.org/blog/claude-haiku-45-le-modle-qui-redfinit-le-rapport-p)

The barrier between "proof of concept" and "production" just got dramatically lower.

What are you planning to build with it?

I’m currently working as an SDET in a product-based company, mainly focused on end-to-end automation testing. Recently, I came across discussions saying many companies no longer prefer QA engineers who only have E2E automation experience, and it honestly made me anxious about my long-term career prospects.

A lot of my work involves:

* E2E automation frameworks
* API testing
* CI/CD deployments in test env
* Test infrastructure and automation pipelines

For experienced engineers/managers here:

* How do you see the future of SDET/QA roles evolving?
* Is deep E2E automation experience still valuable long term?
* What skills should someone in QA automation start building now to stay relevant in the next 5–10 years?
* Would you recommend transitioning toward backend development, infrastructure/platform engineering, or something else?

Thanks in advance (used gpt to format/modify it)

\[title has it all\]