Claude Sonnet 4.5 vs Opus 4.1: Which Model Wins for Coding, Agents, and Long Runs?

TL;DR

• Coding: Sonnet 4.5 claims state-of-the-art on SWE-bench Verified (primary 77.2%; 82.0% with high-compute), positioning it as the “best coding model” right now.
  
• Agents & long runs: Reported 30+ hours of coherent, multi-step autonomy in trials—significant for real workflows.
  
• Computer use: OSWorld leadership at 61.4%, a big jump from Sonnet 4.0.
  
• Enterprise stack: Available now via API and Amazon Bedrock, with AgentCore (session isolation, observability, up to 8-hour managed runs) plus smart context/memory features.
  
• Pricing: Same as Sonnet 4—$3 / $15 per 1M tokens (in/out).

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Introduction

AI models are shipping faster than ever, and the pressure shows up first in real work: coding at repo scale, long-horizon agents, and reliable computer use. Hot on the heels of Opus 4.1, Anthropic’s Claude Sonnet 4.5 arrives with a practical promise: ship production-grade code, keep agents coherent for hours (even days), and operate real tools—without a price hike.

This post compares Sonnet 4.5 and Opus 4.1 where it matters: coding quality and throughput, agent stamina on multi-step tasks, computer-use reliability, enterprise tooling (SDKs, Bedrock/AgentCore), and total cost—so you can pick the right model for your stack. And if you plan to pilot the winner in production, partnering with an experienced Generative AI development company can help you stand up fair A/B evaluations, add guardrails for tool use, and integrate Bedrock/AgentCore or SDKs without derailing timelines.

If you’re still mapping the landscape, this GPT-4o vs Claude 4 comparison covers trade-offs beyond coding, including multimodal considerations.

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Model overview

What is Claude Sonnet 4.5

Anthropic frames Claude Sonnet 4.5 as its most capable release for coding, complex agents, and reliable computer use, with notable gains in reasoning and math. Beyond raw model quality, it arrives as a developer-focused bundle:

• Claude Code upgrades: built-in checkpoints to roll back work, a refreshed terminal experience, and tighter workflows for multi-step coding tasks.
  
• IDE and in-app execution: a native VS Code extension plus in-chat code execution and file creation (spreadsheets, slides, docs) so teams can prototype and validate changes without context switching.
  
• Long-run enablers: context editing and a memory tool in the API to keep long tasks coherent, reduce drift, and manage evolving state across sessions.
  
• Agent platform: the Claude Agent SDK, exposing the infrastructure Anthropic uses internally (state, memory, permissioning, tool orchestration) so you can build durable agents rather than one-off scripts.
  
• Safety posture: released with stronger defenses against prompt injection and reductions in behaviors like sycophancy/deception—important when agents touch production systems.
  
• Pricing and availability: drop-in upgrade priced at $3 / $15 per 1M tokens (input/output), available via API and in the Claude apps; also accessible on major clouds (e.g., Bedrock) where you need enterprise controls.

In short, Sonnet 4.5 is positioned not just as a faster/better model, but as a production workflow upgrade for teams shipping code and running long-horizon agents.

What is Claude Opus 4.1

Released in August 2025, Claude Opus 4.1 is Anthropic’s high-capacity flagship that preceded Sonnet 4.5. It’s widely used for deep reasoning, long-horizon tasks, and complex problem solving where maximal capability is preferred:

• Strengths: excels at nuanced analysis, intricate planning, and multi-step reasoning chains—often favored for research-grade prompts or complex agent policies.
  
• Enterprise availability: exposed via the Anthropic API and major cloud platforms (including Amazon Bedrock) for organizations standardizing on managed security, isolation, and observability.
  
• Where it still competes: depending on your stack, latency targets, and toolchain, Opus 4.1 can remain the better fit—especially if your pipelines, prompts, and guardrails are already tuned for Opus variants.

For background on how Opus and Sonnet have traded leads over time, check our earlier Claude Opus 4 vs Sonnet 4 comparison.

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Headline benchmarks and what they mean (Sonnet 4.5 vs Opus 4.1)

Coding performance

• Claude Sonnet 4.5
  
  • SWE-bench Verified: 77.2% primary; 82.0% with parallel test-time compute (multiple attempts + rejection sampling). This indicates the model can read a repo, implement multi-file patches, and pass hidden tests—closer to how engineers actually ship fixes.
    
  • Why it matters: Higher pass rates usually mean fewer CI ping-pongs, cleaner PRs, and less reviewer rework (e.g., fewer broken imports, missed tests, or config regressions).
    
  • What to verify in-house: Pick 10–20 real issues across services; enforce a tests-first rule (model must write/adjust tests). Track PR acceptance time, test coverage delta, flake rate, and rollback incidents.
    
• Claude Opus 4.1
  
  • Strong at deep reasoning and intricate planning, often favored on repos where prompts lean heavily on long contextual chains or design discussion before patching.
    
  • Where it can still win: If your team already tuned prompts/tooling for Opus (e.g., custom linters, scaffolds), Opus may show lower latency jitter or more consistent architectural reasoning on specific codebases.

Decision hint: If your pain is broken CI and partial fixes, trial Sonnet 4.5 first. If your pain is design-level correctness (e.g., refactoring strategy, migration plans), keep Opus 4.1 in the A/B.

Computer use and tool handling

• Claude Sonnet 4.5
  
  • OSWorld: 61.4% vs Sonnet 4.0’s 42.2%—a sizable jump on real computer tasks: navigating sites, filling spreadsheets, manipulating files, running terminal commands.
    
  • Why it matters: Browser/app agents fail in subtle ways (dom changes, auth flows, flaky buttons). Higher OSWorld typically yields fewer derailments, less token burn from retries, and more stable 6–30h runs.
    
  • Ops note: With context editing + memory (API) and tool-history clearing (on Bedrock), long sessions accumulate less junk, reducing “forgetfulness” and runaway token costs.

If your workflow lives in the browser, our hands-on notes with the Claude for Chrome browser extension show how to wire scraping, sheets, and file ops into real agent runs.

• Claude Opus 4.1
  
  • Competitive for agentic reasoning, but there’s no widely cited lead on OSWorld vs Sonnet 4.5. Still worth testing if your agents are analysis-heavy with occasional tool use (vs UI-heavy automation).

What to simulate: A browser+sheet workflow: login → scrape multiple vendors → normalize → write to a shared sheet → export PDF → email draft. Measure end-to-end success rate, human interventions, tokens/success, and time-to-completion.

Reasoning and domain tasks

• Claude Sonnet 4.5
  
  • Gains reported on math/logic (e.g., AIME) and knowledge breadth (MMMLU), plus strong results on finance-oriented agent tasks (entry-level analyst workflows: tables, reconciliations, memos).
    
  • So what: Many workflows mix code + analysis + documentation. Better reasoning can cut spec churn, produce clearer design notes, and yield audit-friendly outputs for compliance/finance.
    
• Claude Opus 4.1
  
  • Remains a high-capacity long-horizon reasoner. For deep research prompts, multi-step planning, or policy/agent design, Opus may be neck-and-neck (or preferred) depending on prompt style and your guardrails.

Exploring alternatives? Our side-by-side DeepSeek V3.1 vs GPT-5 vs Claude 4.1 highlights where reasoning and cost dynamics diverge across vendors.

Benchmark caveats (apply to both)

• Directional, not definitive: Public scores can be skewed by contamination, scaffolding, or prompt addenda. Use them to shortlist, not to finalize.
  
• Run a fair A/B harness: Keep the same tool budget, retry policy, “thinking”/context limits, stop reasons, and temperature/seed for both models. If you test high-compute on one, test it on both.
  
• Measure production-grade KPIs:
  
  • Engineering: CI pass rate, PR cycle time, test coverage delta, regression count, rollbacks.
    
  • Agents: success rate over 6–30h, tokens/success, unassisted step ratio, recovery after 4xx/5xx, prompt-injection resilience.
    
  • Cost & Ops: token cost per successful task, infra incidents, on-call pages, time to triage failures.
    
• Platform matters: On Amazon Bedrock/AgentCore, features like session isolation, observability, 8-hour managed runs, tool-history clearing, and early-stop explanations can change outcomes—keep platform constant across models when comparing.

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Agents and long-run stability

Sonnet 4.5 agent stamina

Early reports indicate Claude Sonnet 4.5 can stay coherent for 30+ hours on complex, multi-step projects—e.g., planning and building an app, provisioning databases, purchasing domains, and even running basic compliance checks. Two design choices make those long horizons practical:

• Memory + context editing: lets the agent retain key facts while pruning stale details, reducing “context bloat” and off-topic drift over time.
  
• Smarter tool use: fewer redundant calls and better sequencing, which lowers token burn and prevents “tool spam” from overwhelming the context window.

In practice, that means fewer mid-run resets and higher odds that a multi-phase workflow (plan → implement → validate → document) completes without human babysitting.

Opus 4.1 agent profile

Claude Opus 4.1 remains a high-capacity long-horizon reasoner. Teams that already tuned prompts, scaffolds, and retry policies around Opus often see:

• Stable chain-of-thought planning for intricate migrations or research tasks.
  
• Consistent latency on their existing infra and tooling.
  If Opus is your incumbent and performs well on your repos, it absolutely deserves a head-to-head against Sonnet 4.5—especially on deeply analytical or policy-driven agent tasks.

What long runs need in production

Whether you choose Sonnet 4.5 or Opus 4.1, durable agents don’t survive on model quality alone. You’ll want an ops layer that provides:

• Granular permissions: explicit allowlists for tools, data stores, and external actions.
  
• Subagent coordination: clear roles (planner, executor, verifier) and handoff rules.
  
• Observability: traces for prompts, tool I/O, tokens over time, failure points, and human handoffs.
  
• Rate limiting and backoff: to avoid ban loops and API thundering herds.
  
• Failure recovery: checkpoints, rollbacks, resumable runs, and “ask-for-help” gates.

Here, Sonnet 4.5 arrives with two helpful accelerants:

• Claude Agent SDK: production-oriented primitives (state, memory, permissioning, tool orchestration) so you can build resume-safe workflows and coordinate subagents without writing everything from scratch.
  
• Amazon Bedrock + AgentCore (when deployed on Bedrock): session isolation, observability, 8-hour managed long-running support, and tool-history clearing/early-stop explanations—all of which reduce context creep, control token costs, and make long sessions more predictable.

How to evaluate (quick checklist)

Run both models on the same harness and score the following over 6–30 hours:

• Task success rate (start → done without human intervention)
  
• Mean time to recovery after a tool/API error
  
• Tokens per successful run and tool-call density (are you paying for loops?)
  
• Checkpoint usefulness (can the agent resume after a crash or approval gate?)
  
• Security events avoided (prompt-injection attempts blocked, forbidden actions prevented)

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Pricing, latency, and total cost of ownership

Price parity that actually matters

• Claude Sonnet 4.5 keeps $3 per 1M input / $15 per 1M output tokens—same as Sonnet 4.
  
• Opus 4.1 is generally in a similar enterprise price band; confirm your SKU/region.

Back-of-napkin:
Cost ≈ (input÷1M×$3) + (output÷1M×$15).
Example: 4M in + 1M out ≈ $27 per job (platform fees excluded).

Latency and throughput

• Sonnet 4.5: built for day-to-day dev loops and agents; memory/context editing tends to reduce retries and context churn, stabilizing p95 latency on tool-heavy tasks.
  
• Opus 4.1: capacity-first; some stacks report steadier latency for long, analysis-heavy prompts. Measure p95/p99 and tokens per successful task for both.

Hidden costs to watch

• Tool churn → token burn (duplicate scraping, repeat tests).
  
• Retries on long horizons (naive policies silently double tokens).
  
• Human checkpoints (pause/resume can re-inflate context).
  
• DIY ops overhead vs managed Bedrock/AgentCore (session isolation, 8-hour managed runs, observability, tool-history clearing, early-stop reasons).

Cost controls: dedupe/caching tool outputs, strict step limits, deterministic temps for execution steps, batch compile/test phases, progressive context trimming.

Side-by-side comparison

Dimension	Sonnet 4.5	Opus 4.1
Coding (SWE-bench Verified)	77.2% primary; 82.0% high-compute	Comparable long-horizon coding claims; verify on your repos
Computer Use (OSWorld)	61.4%	Not publicly leading on OSWorld at time of writing
Long-Run Stability	Observed 30+ hrs coherent multi-step runs	Strong long-horizon reasoning; verify stability on your stack
Agent Stack	Claude Agent SDK, memory, context editing	Enterprise-ready model; depends on your toolchain
Bedrock/AgentCore	Available; isolation, observability, up to 8-hour managed runs	Available via Bedrock; similar ops benefits
Safety/Alignment	Anthropic: improved anti-sycophancy, PJI defenses; ASL-aligned approach	Anthropic safety posture; compare classifiers in your domain
Price	$3 / $15 per 1M tokens	Similar order of magnitude; confirm current SKU terms

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When to choose which

Pick Sonnet 4.5 if…

• You need repo-scale coding with tight dev loops. The native VS Code extension plus in-chat code execution and file creation help you iterate without context switching—great for multi-file refactors, test updates, and CI validation.
  
• Your roadmap depends on browser/app agents that run 6–30 hours. The OSWorld lead and long-run reports point to fewer derailments on tool-heavy workflows (scraping → transforming → reporting) over extended sessions.
  
• You want enterprise guardrails out of the box. Deploying on Amazon Bedrock with AgentCore gives you session isolation, observability, and managed long-running support, making production agents easier to monitor and govern.

If you’re still weighing vendor ecosystems, this GPT-4o vs Claude 4 overview summarizes non-coding trade-offs that may affect your stack choice.

Pick Opus 4.1 if…

• Your stack already performs better on Opus. If you see lower latency/variance or fewer regressions on your repositories—especially for deep, single-threaded reasoning or policy/design prompts—stick with Opus for those paths.
  
• Switching costs are high mid-project. If your Bedrock integrations, prompts, guardrails, and CI scaffolds are tuned for Opus variants, finishing the current deliverables on Opus can be cheaper and safer.

On paper, Claude Sonnet 4.5 is the pragmatic default for today’s production needs—repo-scale coding, reliable computer use, and long-run agent work—while Opus 4.1 still earns a seat for deep, single-threaded reasoning and stacks already tuned around it. But leaderboards don’t ship features—your A/B results do. The right pick is the model that delivers the lowest $ per successful outcome on your codebases and workflows.

If you’re moving from comparison to action, start with a two-week pilot:

• Run both models on identical scaffolding (same tool budgets, retry policy, stop reasons).
  
• Track CI pass rate, PR cycle time, tokens/success, p95 latency/variance, and unassisted success over 6–30h agent runs.
  
• Keep platform variables constant (e.g., Bedrock/AgentCore) and use context editing, tool-history clearing, and checkpoints to control drift and cost.

When you’re ready to stand this up in production without derailing timelines partnering with a seasoned generative AI development company can add real value: building a fair eval harness, hardening tool permissions and prompt-injection defenses, wiring Bedrock/AgentCore or the Claude Agent SDK into your stack, and instrumenting dashboards so you can prove ROI beyond leaderboard screenshots.

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FAQ

Does Sonnet 4.5 replace Opus 4.1 for all coding tasks?
No. Treat Sonnet 4.5 as a new default to test—but keep Opus 4.1 in the harness. Winners vary by repo, test budget, and runtime constraints.

How do I avoid context-limit failures on long runs?
Use context editing, tool-history clearing, and cross-conversation memory. Bedrock surfaces early-stop reasons and lets you trim older tool outputs to stay under limits. Amazon Web Services, Inc.

What’s the fastest path to pilot on Bedrock?
Use Bedrock Converse API and an inference profile; pair with AgentCore for isolation/observability, then scale. Amazon Web Services, Inc.

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