Composer 1.5 vs Claude Opus 4.6 in Cursor Agent Mode: Which Wins?

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Composer 1.5 vs Claude Opus...

TL;DR

Agent Mode winner depends on your workflow: it is about fewer retries, fewer broken builds, and faster time-to-merge, not “best model overall.”
Choose Composer 1.5 for daily Cursor work: fast and interactive, trained with 20× more RL, uses thinking tokens to plan, and self-summarizes to stay on track in long tasks.
Choose Claude Opus 4.6 for high-stakes and large-repo work: stronger for deep reasoning and cross-file dependency tracing, with 1M context in Max Mode when you need repo-wide understanding.
Context trade-off: Composer keeps going by summarizing when memory fills, while Opus can keep more raw code in memory (especially at 1M), reducing “guesswork by chunking.”
Cost trade-off in Cursor: Composer 1.5 is cheaper per token ($3.5/$17.5) than Opus 4.6 ($5/$25), so use Composer as default and reserve Opus for premium tasks like audits, migrations, and repo-wide refactors.

What Agent Mode actually does in Cursor

Cursor Agent Mode is not just chat. It is a workflow engine. You give it a goal, and it tries to execute it across your codebase by doing things like:

scanning relevant files and project structure
planning steps and sequencing work
editing multiple files (often across layers)
iterating when something breaks or is missing

So the model is not only writing code. It is making decisions: what to change, where to change it, and how to avoid breaking your app.

That is why model choice matters. The editor experience is the same, but the “brain” you plug into Agent Mode changes:

how well it plans multi-step work
how safely it edits across many files
how it handles long-running tasks without losing context
how many retries you need to get to a clean PR

Quick positioning: What each model is built for

Composer 1.5

Composer 1.5 is Cursor’s latest agentic coding model built for day-to-day use inside the editor. Cursor positions it as a strong balance of speed and intelligence for interactive work.

What makes Composer 1.5 different from Composer 1 is not just small tuning. Cursor says it scaled reinforcement learning about 20×, and that much of the gain shows up on hard, multi-step problems.

In practical terms, Composer 1.5 is built to:

stay fast for everyday tasks
think longer for complicated tasks
support agentic workflows without feeling slow

A simple mental model is: Composer 1.5 is optimized for “shipping” inside Cursor.

Claude Opus 4.6

Claude Opus 4.6 is a frontier model known for deeper reasoning and long-context work. Inside Cursor, Opus is available with:

200K context by default
up to 1M context in Max Mode

Opus is not positioned as “fastest.” It is positioned as “most capable for complex reasoning, large codebase analysis, and higher-stakes work.”

A simple mental model is: Opus 4.6 is optimized for correctness and depth when the repo is big and the task is risky.

Read More: Codex 5.3 vs Opus 4.6

What changed in Composer 1.5 and why it matters for Agent Mode

Composer 1.5 is not just “Composer 1, but slightly better.” Cursor is basically saying: we trained it much harder, taught it to plan better, and gave it a way to not lose track during long jobs. In Agent Mode, those three things directly affect whether the agent finishes the task cleanly or gets confused halfway.

1) 20× reinforcement learning scale (why that helps in real work)

Reinforcement learning (RL) is like training by practice + feedback.

Instead of only learning from examples, the model is trained by doing tasks and getting signals like:

“that fix worked”
“that broke tests”
“that plan was wrong”
“that answer was incomplete”

Cursor says Composer 1.5 got about 20× more of this practice than Composer 1.

What that means inside Agent Mode

Agent Mode tasks are usually not single-step. They are more like:

update one file
then update another file
then fix errors that appear
then adjust config
then rerun

A weaker model often fails because it:

makes a plan too quickly
starts editing without fully understanding dependencies
hits an error and does not recover well
“thinks it’s done” when it is only halfway done

With more RL training, Composer 1.5 is more likely to:

avoid getting stuck mid-way (“dead ends”)
keep the bigger picture in mind (long-horizon planning)
produce changes that actually run, not just look correct

Simple example

You ask: “Add role-based access to my app.”

A weaker agent might protect only the frontend pages and forget API routes.

Composer 1.5 is trained to catch more of these “real-world gotchas” because RL rewards outcomes that actually work end-to-end.

2) “Thinking tokens” for planning (why it reduces messy edits)

Cursor calls Composer 1.5 a “thinking model.” In normal human terms:

It pauses to plan before it starts touching your code.

These “thinking tokens” are internal steps the model uses to:

look at your folder structure
identify the right files
figure out dependencies
decide the order of changes
anticipate likely errors

Why this matters in Agent Mode

Agent Mode is dangerous when a model:

edits the wrong file first
changes patterns that don’t match your codebase
makes 5 edits quickly, then you realize 3 were unnecessary

Planning first reduces that.

Where you feel the difference

big refactors across many files
features that touch frontend + backend + database
changes that must follow your existing conventions

Simple example

You ask: “Refactor auth middleware across the repo.”

Without good planning, an agent may update some middleware but miss other entry points.

With better planning, the agent first identifies all the “touch points” (routes, guards, API layers) and then edits with fewer surprises later.

3) Self-summarization for long-running tasks (how it prevents “getting lost”)

This solves a very common Agent Mode problem: long tasks make the model forget what happened earlier.

Every model has a context limit. As the task grows, the conversation + files + outputs can fill up memory.

When that happens, weaker models:

forget what they already changed
repeat work
contradict earlier decisions
miss steps that were planned but not finished

Composer 1.5 has a built-in trick: When context is getting full, it creates a short summary of what’s done and what’s left, then continues using that summary as its “memory.” This can happen multiple times.

Why it matters in Agent Mode

Long tasks often include:

multiple files
multiple rounds of debugging
several errors and fixes
configuration + docs + tests

If the agent loses track, the task becomes chaotic.

Simple example

You ask: “Implement payments + invoices + webhook handling.”

Halfway through, the agent already:

added schema changes
created API routes
started webhook logic

If it forgets those details, it may:

re-add the same migration
overwrite the route structure
introduce duplicate handlers

Self-summarization is Cursor’s way of keeping the agent “aware” of progress without needing a huge 1M context window every time.

Composer 1.5 improves Agent Mode because it is trained to finish multi-step work more reliably: it practices harder (20× RL), plans before editing (thinking tokens), and stays on track during long tasks (self-summarization).

Context windows in Cursor: 200K default vs 1M Max Mode

Cursor provides a useful frame: the default context window is typically 200K tokens, which they equate to roughly ~15,000 lines of code.

Here is the practical difference in Agent Mode:

When 200K is enough

feature changes touching a small part of the codebase
routine bug fixes
refactors that stay within a bounded module
adding a single integration with clear boundaries

This is the “daily work” zone where Composer 1.5 is designed to be strong.

When 1M context becomes a real advantage

large repositories where the bug spans multiple modules
migrations and refactors that require consistency across layers
audit-style work: permissions, auth, security checks, compliance reviews
situations where chunking causes missed dependencies

This is where Opus 4.6 in Max Mode can justify its higher cost: it reduces fragmentation and “guesswork by chunking.”

Composer vs Opus approach to long tasks

Composer’s approach: keep working by summarizing state when context fills
Opus approach: keep more raw repo context available (especially at 1M), reducing the need to compress

Cost comparison in Cursor: what you actually pay

Cursor pricing is simple in concept: your plan includes usage, and that usage is consumed at the model’s API rates. So model choice directly affects how long your included credits last.

Composer 1.5 (Cursor rates)

Input: $3.5 / MTok
Output: $17.5 / MTok
Cache read: $0.35 / MTok

Claude Opus 4.6 (Cursor rates)

Input: $5 / MTok
Output: $25 / MTok
Cache write: $6.25 / MTok
Cache read: $0.5 / MTok

What this means in plain terms

Composer 1.5 is cheaper for day-to-day Agent Mode usage
Opus costs more per token, but the value shows up when it avoids rework in large, complex tasks
If you frequently need Max Mode to reach 1M context, treat that as a premium workflow, not an always-on default

What “performance” really means in Agent Mode

In Cursor Agent Mode, “performance” does not mean who writes the nicest code snippet or who wins a random benchmark. It means one practical thing:

Which model helps you finish real work end to end with fewer retries and less cleanup?

Agent Mode is doing multi-step execution across your repo. So the best model is the one that:

follows the right plan
edits the right files safely
handles long tasks without getting confused
gets you to a merge-ready PR faster

Here are the performance signals that actually matter for Agent Mode.

A) Terminal and execution workflows

Many Agent Mode tasks are basically “developer chores” that live around the command line:

running tests and fixing failures
resolving dependency and lockfile issues
handling build tooling problems
debugging CI failures
running scripts and setup steps

In Cursor Agent Mode, “performance” simply means how easily the model helps you finish real work. If your tasks include lots of command line actions like running tests, fixing build errors, resolving git conflicts, or debugging CI, then terminal-focused benchmarks can give a rough hint about which model handles execution better. But since Cursor only mentions Terminal-Bench results for Composer 1.5, the safest approach is to avoid guessing numbers and instead run a small pilot on your own repo tasks to see which model needs fewer retries and gets you to a clean PR faster.

B) Long-horizon stability (not losing the thread mid-task)

Agent Mode success is mostly about staying consistent during long jobs. A task can easily involve 10–30 steps, and models fail when they forget:

what they already changed
what is still pending
why earlier decisions were made

This is where Composer and Opus take different paths:

Composer 1.5 uses self-summarization so it can keep going when context fills up.
Opus 4.6 can rely on large raw context, especially with 1M Max Mode, reducing the need to compress.

If your Agent Mode runs often derail halfway, this stability factor matters more than any single benchmark.

C) Rework and “time-to-merge” (the real scorecard)

The most important metric is not a benchmark score. It is how much rework your team had to do after the agent ran.

Track these four things across a small set of real tasks:

how many retries were needed to get a working patch
how often builds/tests broke
how many reviewer edits were required before merge
how often the model missed cross-file dependencies

Whichever model produces fewer retries and less cleanup is the real “winner” for Agent Mode, even if another model looks better on paper.

Who wins in Cursor Agent Mode

Composer 1.5 wins when your work looks like this

lots of small PRs and rapid iteration
routine feature work and refactors
multi-file edits where speed matters
interactive development where you want fast back-and-forth

Why it wins: Composer 1.5 is built for daily interactive use, cheaper per token, and tuned for agentic multi-step work without feeling slow.

Opus 4.6 wins when your work looks like this

large codebase analysis across many modules
migrations and architecture refactors where correctness matters more than speed
audit-style tasks like auth, permissions, and security reviews
tasks where you benefit from Max Mode 1M context to avoid chunking

Why it wins: Opus is better suited for deep reasoning and cross-file dependency tracing, and Max Mode gives it a context advantage.

Decision matrix: pick based on your bottleneck

Here is the simplest way to choose.

Bottleneck: speed and throughput → choose Composer 1.5
Bottleneck: repo size and context fragmentation → choose Opus 4.6 (Max Mode)
Bottleneck: long-running tasks that lose the thread → test Composer self-summarization vs Opus long context
Bottleneck: cost efficiency inside Cursor usage credits → choose Composer 1.5 for default work and reserve Opus for premium tasks

Best practice: use both with simple task routing

Many teams will get the best outcome by routing tasks:

A practical routing rule

Use Composer 1.5 for daily Agent Mode work: fixes, routine features, refactors, fast iterations
Use Opus 4.6 for deep work: audits, migrations, repo-wide changes, high-stakes correctness

What to track for 2 weeks

If you want to make the decision quickly, run a lightweight pilot and track:

success rate on first attempt
retries per task
reviewer edits needed
cost consumed per task type

You will learn more from that than from any public benchmark.

Conclusion

If the question is “Which model wins for Agent Mode in Cursor?”, the honest answer is: it depends on what you do most.

Composer 1.5 is the better default for most teams because it is built for daily interactive use, is cheaper, and is tuned for multi-step agent workflows inside Cursor.
Claude Opus 4.6 becomes the better choice when tasks are context-heavy and high-risk, especially when Max Mode 1M context prevents missed dependencies and reduces rework.

The strongest setup is not picking one model forever. It is routing: speed for daily work, depth for high-stakes tasks.