by Anthropic · Claude 4 family · best for the Opus price reset, stable target
Claude Opus 4.5, released November 24, 2025, is the model that re-priced the Opus tier — dropping input from $15 to $5 and output from $75 to $25, the pricing that has held through Opus 4.6 and 4.7. It paired that cut with a capability jump (SWE-bench Verified 80.9%, the first Opus to break 80%) and Anthropic's strongest alignment profile to date. For a buyer, the single sentence is this: the historically pivotal Opus model whose pricing reset made Opus-tier capability viable for daily use — now superseded twice, but still a stable, fully supported target.
effort parameter for explicit speed-vs-capability trade-off.| Benchmark | Score | Source |
|---|---|---|
| Humanity's Last Exam | 43.4% | vellum.ai 2025-11-24T00:00:00.000Z |
| MMLU | 90.8% | vellum.ai 2025-11-24T00:00:00.000Z |
| MMMU | 80.7% | vellum.ai 2025-11-24T00:00:00.000Z |
| MMLU-Pro | 90% | artificialanalysis.ai 2025-11-24T00:00:00.000Z |
| HumanEval | 92% | automatio.ai 2025-11-24T00:00:00.000Z |
| TAU-bench | 88.9% | vellum.ai 2025-11-24T00:00:00.000Z |
| LMArena Elo | 1468 | openlm.ai 2026-05-28T00:00:00.000Z |
| GPQA Diamond | 87% | vellum.ai 2025-11-24T00:00:00.000Z |
| Terminal-Bench | 59.8% | vellum.ai 2025-11-24T00:00:00.000Z |
| LMArena Coding Elo | 1510 | openlm.ai 2026-05-28T00:00:00.000Z |
| SWE-bench Verified | 80.9% | vellum.ai 2025-11-24T00:00:00.000Z |
| Artificial Analysis Index | 43 | artificialanalysis.ai 2025-11-24T00:00:00.000Z |
Six personas, six verdicts — the same panel that reviews every product on TopReviewed.
“Opus 4.5 was the inflection point — the 3x price cut changed the Opus deployment math for good.”
Opus 4.5 changed the strategic calculus for the Opus tier: the cut from $15/$75 to $5/$25 made frontier Opus capability viable for daily use, and that price still anchors the family. For new workloads in mid-2026 the question is whether to go to 4.6 (1M context, better ARC-AGI-2) or 4.7 (better SWE-bench, vision) — either is the strategically correct choice for new builds. Continued use of 4.5 is reasonable in production windows with tuned prompt suites and a controlled migration path. Multi-cloud availability is unchanged.
“Opus 4.5's 3x price cut was the strategic masterstroke that reset the entire frontier's pricing expectations.”
Opus 4.5's market significance is hard to overstate: by tripling Opus affordability overnight while raising capability, Anthropic reset buyer expectations for what frontier intelligence should cost and pressured competitors on price-to-capability. It also led on alignment, a differentiator that matters to enterprise and regulated buyers. As a standalone product its capability has been surpassed, but its pricing legacy defines the tier and its safety positioning still resonates with risk-averse adopters.
“This is the model that made Opus affordable — and on rate card it's identical to 4.6 and 4.7 today.”
Opus 4.5 is the model that made Opus-tier work financially feasible; the November 2025 reset to $5/$25 is the pricing that still anchors the tier. On TCO it is identical to 4.6/4.7 on headline rates, with matching cache and batch discounts, and its token-efficiency focus can make it cheaper per task than peers that emit more tokens. The financial case to migrate to 4.6/4.7 is the absence of any cost downside combined with capability upside — there is no money reason to delay migration on cost grounds.
“The first Opus that felt economically viable for daily agent use — SWE-bench 80.9% still holds up.”
For builders, Opus 4.5 was the first Opus model that felt economically viable for daily agent use, and SWE-bench Verified 80.9% remains competitive even now. The effort parameter is useful but less polished than the adaptive thinking shipped with 4.6. The 200k context cap is the real constraint — long-repo work pushes you to 4.6 or later. Tool use is unchanged across the family. For maintaining existing 4.5 integrations it is fine; for new builds, go to 4.7.
effort less polished than adaptive thinking“Polished and safe — on casual chat most users can't tell 4.5 from the newer Opus models.”
For a consumer chat product, Opus 4.5 delivers a polished experience: moderate latency, high conversation quality, calibrated and notably safe refusals. End users will not perceive a difference between 4.5, 4.6, and 4.7 on casual chat. Where the gap shows is hard reasoning and computer use, both of which improved in 4.6 and again in 4.7. The May 2025 reliable cutoff is dated for current events; web search mitigates. The standout user-facing trait is trustworthiness — this was Anthropic's most aligned model.
“A landmark for pricing, not capability — and its ARC-AGI-2 of 37.6% was halved by the very next release.”
Opus 4.5's claims were honest and its alignment leadership is genuinely verifiable (the ~4.7% prompt-injection number is a real, useful datapoint). The skeptical caveat is that its fame is about price, not raw capability: ARC-AGI-2 at 37.6% was nearly doubled by Opus 4.6's 68.8% just ten weeks later, and the 200k context plus May 2025 cutoff now look dated. The "AIME 100% with tools" framing flatters it. There is no capability or cost case for new work here versus 4.6/4.7; it earns its score on safety and historical significance.
effort parameter only.The full research notes behind this review — verified against primary sources.
Anthropic discloses no parameter count, layer count, or attention mechanism — null/unknown. Disclosed: a 200k-token context window (the 1M context arrived with Opus 4.6), 64k max output, and an explicit effort parameter for tuning capability vs latency (adaptive thinking came with 4.6). It uses the standard pre-4.7 Claude tokenizer. Token efficiency was a headline engineering focus — Opus 4.5 reached its Intelligence Index score using markedly fewer output tokens than competing frontier models.
Coding (9.0): SWE-bench Verified 80.9% (first Opus over 80%), HumanEval 92%, LMArena coding Elo 1510. Reasoning (8.8): GPQA Diamond 87.0%, MMLU 90.8%, MMLU-Pro 90% (tied Gemini 3 Pro), Terminal-Bench Hard 44% (highest at release), HLE with tools 43.4%. Math (8.5): strong, AIME 2025 100% with Python tools per Anthropic. Agentic/tool use (9.0): full first-party tool suite, Tau2-bench retail 88.9%, OSWorld 66.3%, Terminal-Bench 59.8%. Long-context (7.5): 200k window only. Multilingual (9.0): MMLU multilingual 90.8%. Vision (8.5) and document/OCR (8.3): MMMU 80.7%. Instruction-following (9.0): strong. Function-calling (9.0): robust. Safety calibration (9.5): the standout — "most robustly aligned" Anthropic model at release, ~4.7% prompt-injection success rate. Realtime-data (6.5): May 2025 cutoff plus web search/fetch.
| Benchmark | Score | vs Predecessor | vs Successor | Source |
|---|---|---|---|---|
| SWE-bench Verified | 80.9% | +6.4 vs Opus 4.1 (74.5%) | ~flat vs Opus 4.6 (80.8%) | Vellum |
| GPQA Diamond | 87.0% | improved | behind Opus 4.6 (91.3%) | Vellum |
| MMLU (multilingual) | 90.8% | improved | frontier tier | Vellum |
| MMLU-Pro | 90.0% | improved | tied Gemini 3 Pro | AA |
| MMMU | 80.7% | improved | strong vision tier | Vellum |
| Terminal-Bench 2.0 | 59.8% | improved | behind Opus 4.6 (65.4%) | Vellum |
| Tau2-bench Retail | 88.9% | improved | behind Opus 4.6 (91.9%) | Vellum |
| OSWorld | 66.3% | improved | behind Opus 4.6 (72.7%) | Vellum |
| ARC-AGI-2 | 37.6% | n/a | behind Opus 4.6 (68.8%) | Vellum |
| HLE (with tools) | 43.4% | improved | behind Opus 4.6 (53.1%) | Vellum |
| HumanEval | 92% | improved | near-saturated | Automatio |
| LMArena Elo | 1468 | improved | behind Opus 4.6 (1490) | OpenLM |
| LMArena Coding Elo | 1510 | improved | behind Opus 4.6 (1535) | OpenLM |
| Artificial Analysis Index | 43 (non-reasoning) | improved | behind Opus 4.6 (53) | AA |
(AIME 2025, MATH-500, LiveCodeBench, Aider Polyglot, IFEval, BBH, MRCR, SimpleQA carry no clean published Opus-4.5 figure and are null. The AA Index 43 is the current-scale non-reasoning figure; AA's earlier article cited a higher number on a prior index scale.)
Output speed is ~53.2 tokens/sec with time-to-first-token ~1.58s (Artificial Analysis), placing it in the slow tier relative to Sonnet/Haiku though with a better TTFT than Opus 4.7's adaptive max-effort mode. The token-efficiency focus means it often reaches a good answer with fewer output tokens than peers, which partly offsets the modest throughput. It is a deliberate model suited to hard work and batch.
| Surface | Cost | Notes |
|---|---|---|
| API input | $5 / 1M tok | The reset rate, same as Opus 4.6/4.7 |
| API output | $25 / 1M tok | Same as Opus 4.6/4.7 |
| Cached input (read/hit) | $0.50 / 1M tok | 0.1x base |
| Cache write (5m / 1h) | $6.25 / $10 per 1M tok | 1.25x / 2x base |
| Batch (in/out) | $2.50 / $12.50 per 1M tok | 50% off both |
| Web search tool | $10 / 1,000 searches | plus token costs |
| Direct UI | $20/mo Pro · $100/mo Max 5x · $200/mo Max 20x | claude.ai |
| Free tier | none for Opus on API | one-time API trial credits only |
| Rate limits | Tiered (Tier 1–4 + Enterprise) | Priority Tier supported |
Proprietary, no open weights or self-hosting. First-party via the Claude API and Claude Platform on AWS, plus Amazon Bedrock (global and regional endpoints — Opus 4.5 was among the first with global vs regional endpoints), Google Vertex AI (global, multi-region, regional), and Microsoft Foundry. Regional/multi-region endpoints carry a 10% premium. Data residency options include US and global.
Governed by Anthropic's RSP v3.0 and deployed under ASL-3 protections. No training on API inputs by default; opt-out and zero-retention available. Compliance: SOC 2 Type II, ISO 27001:2022, ISO/IEC 42001:2023, HIPAA (BAA available), GDPR. Anthropic flagged Opus 4.5 as its "most robustly aligned" model at release, with a prompt-injection attack success rate of ~4.7% — the strongest safety calibration of any model in this set. No forced content-moderation classifier.
SDKs in Python, TypeScript, Java, Go, Ruby, and C#. Works with the Claude Agent SDK, Claude Code, LangChain, LlamaIndex, Vercel AI SDK, and Pydantic AI; selectable in Cursor, GitHub Copilot, and Windsurf. Popularity is mainstream, with a meaningful base still in production migration to 4.6/4.7.
It set the $5/$25 Opus pricing that 4.6 and 4.7 still use, and it has the strongest alignment profile of the set.
No — go to Opus 4.7 (or 4.6 for tokenizer stability) at the same price with more capability.
The 200k context and the May 2025 cutoff, both improved in later Opus models.
Exceptionally — "most robustly aligned" at release, ~4.7% prompt-injection success, SOC 2 Type II, ISO 27001/42001, HIPAA BAA, GDPR.
First-party Claude API plus Bedrock, Vertex AI, and Microsoft Foundry with regional endpoints.
The 3x Opus price cut, the effort parameter, and Anthropic's strongest alignment work to date.
Primary references used to verify this review.
Does not train on API inputs by default
Last verified 2026-05-27