Claude Opus 5
AnthropicKey claude-opus-5Also reported as anthropic/claude-opus-5, router_client:claude/claude-opus-5, kiro/claude-opus-5, teamclaude/claude-opus-5, claude/claude-opus-5, cbai/claude-opus-5, devin/claude-opus-5, vilao/ccf/claude-opus-5, cursor/claude-opus-5, orcarouter/anthropic/claude-opus-5, my anthropic sub/claude-opus-5, pve-claude-mjlee/claude-opus-5, router_client:unknown/claude-opus-5, aion/claude-opus-5, hr-kr/claude-opus-5, a6/claude-opus-5, th/claude-opus-5, vilao/claude-opus-5, s6o/claude-opus-5, sekai/claude-opus-5
- Rank
- #14
- by active users
- Active users
- 50
- Down 18 from 68 active users in the previous 7 days. vs previous 7 days
- Adoption
- 8.2%
- of 610 accounts
- Tokens
- 17.9B
- cache included
- Est. cost
- $15.7K
- at public list prices
- First seen
- Jul 6, 2026
- in any submission
Nov 6–12, 2026 (UTC)610 accounts100% of tokens from an identified modelData through Nov 12, 2026, 08:00 UTCHow we count
Daily active users
Distinct accounts that used this model on each UTC day.
4 active users on Nov 12, 2026
Show daily values
| Date (UTC) | Active users | Tokens |
|---|---|---|
| Nov 6, 2026 | 24 | 1.8B |
| Nov 7, 2026 | 18 | 3B |
| Nov 8, 2026 | 20 | 5.6B |
| Nov 9, 2026 | 23 | 3.8B |
| Nov 10, 2026 | 17 | 2.4B |
| Nov 11, 2026 | 13 | 1.2B |
| Nov 12, 2026 | 4 | 87.6M |
Token mix
How the 17.9B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.
- Input2.2%
- Output0.4%
- Cache read95%
- Cache write2.5%
- Reasoning<0.1%
Agents that carry Claude Opus 5
Each agent's share of this model's tokens, and how many accounts used the model through it.
Claude Code90% of this model's tokens42active users
Senpi (OmO Native)7.1% of this model's tokens5active users
Hermes Agent1.5% of this model's tokens3active users
OpenCode1.4% of this model's tokens1active users
Grok Build<0.1% of this model's tokens1active users
Aside<0.1% of this model's tokens1active users
Pi<0.1% of this model's tokens2active users
Benchmarks
The best result for Claude Opus 5 in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark. Agent rows also show Tokscale usage through that agent, side by side with the score. Usage does not explain the score.
- Epoch Capabilities IndexOverall · Epoch AI164.7
Epoch Capabilities Index: 164.7
- Model
- Claude Opus 5
- Listed as
- Claude Opus 5
- Conditions
- Not reported
- Interval
- 162.1–167.5
- Unit
- ECI
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #10 of 158 matched modelsNo conditions reportedModel released Jul 24, 2026Source: epoch.ai (opens in a new tab) - Terminal-Bench 4.1Agentic coding · Terminal-Bench53.3%
Terminal-Bench 4.1: 53.3%
- Model
- Claude Opus 5
- Listed as
- Opus 5
- Conditions
- XHigh · Claude Code
- Interval
- 50.2–56.4%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Best of 5 reported results for this model.
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
Rank #6 of 23 matched modelsXHigh · Claude CodePublished Nov 3, 2026Source: tbench.ai (opens in a new tab)
Tokscale usage: Claude Code carried 90% of Claude Opus 5 tokens in the last 7 days (42 active users).Show 4 more results with other run conditionsHide the other results
- Listed as Opus 552.1%
Terminal-Bench 4.1: 52.1%
- Model
- Claude Opus 5
- Listed as
- Opus 5
- Conditions
- Max · Claude Code
- Interval
- 48.7–55.5%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
- Listed as Opus 549.7%
Terminal-Bench 4.1: 49.7%
- Model
- Claude Opus 5
- Listed as
- Opus 5
- Conditions
- High · Claude Code
- Interval
- 46.0–53.4%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
- Listed as Opus 545.1%
Terminal-Bench 4.1: 45.1%
- Model
- Claude Opus 5
- Listed as
- Opus 5
- Conditions
- Medium · Claude Code
- Interval
- 41.3–49.0%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
- Listed as Opus 534.8%
Terminal-Bench 4.1: 34.8%
- Model
- Claude Opus 5
- Listed as
- Opus 5
- Conditions
- Low · Claude Code
- Interval
- 30.9–38.8%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
- CursorBenchAgentic coding · Cursor, collected by Epoch AI46.6%
CursorBench: 46.6%
- Model
- Claude Opus 5
- Listed as
- Opus 5 Max
- Conditions
- Max
- Unit
- score
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Best of 5 reported results for this model.
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Show 4 more results with other run conditionsHide the other results
- Listed as Opus 5 Extra High46.1%
CursorBench: 46.1%
- Model
- Claude Opus 5
- Listed as
- Opus 5 Extra High
- Conditions
- XHigh
- Unit
- score
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as Opus 5 High44.7%
CursorBench: 44.7%
- Model
- Claude Opus 5
- Listed as
- Opus 5 High
- Conditions
- High
- Unit
- score
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as Opus 5 Medium43.3%
CursorBench: 43.3%
- Model
- Claude Opus 5
- Listed as
- Opus 5 Medium
- Conditions
- Medium
- Unit
- score
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as Opus 5 Low40.7%
CursorBench: 40.7%
- Model
- Claude Opus 5
- Listed as
- Opus 5 Low
- Conditions
- Low
- Unit
- score
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- DeepSWEAgentic coding · Datacurve, collected by Epoch AI73.6%
DeepSWE: 73.6%
- Model
- Claude Opus 5
- Listed as
- claude-opus-5 (max)
- Conditions
- Max · mini-swe-agent
- Interval
- 69.8–77.5%
- Unit
- pass@1
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Best of 5 reported results for this model.
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #3 of 26 matched modelsMax · mini-swe-agentModel released Jul 24, 2026Source: deepswe.datacurve.ai (opens in a new tab)Show 4 more results with other run conditionsHide the other results
- Listed as claude-opus-5 (xhigh)73.2%
DeepSWE: 73.2%
- Model
- Claude Opus 5
- Listed as
- claude-opus-5 (xhigh)
- Conditions
- XHigh · mini-swe-agent
- Interval
- 70.1–76.2%
- Unit
- pass@1
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as claude-opus-5 (high)72.8%
DeepSWE: 72.8%
- Model
- Claude Opus 5
- Listed as
- claude-opus-5 (high)
- Conditions
- High · mini-swe-agent
- Interval
- 70.9–74.8%
- Unit
- pass@1
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as claude-opus-5 (medium)68.9%
DeepSWE: 68.9%
- Model
- Claude Opus 5
- Listed as
- claude-opus-5 (medium)
- Conditions
- Medium · mini-swe-agent
- Interval
- 67.7–70.1%
- Unit
- pass@1
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as claude-opus-5 (low)58.1%
DeepSWE: 58.1%
- Model
- Claude Opus 5
- Listed as
- claude-opus-5 (low)
- Conditions
- Low · mini-swe-agent
- Interval
- 55.8–60.5%
- Unit
- pass@1
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- FrontierSWEAgentic coding · FrontierSWE, collected by Epoch AI52.0%
FrontierSWE: 52.0%
- Model
- Claude Opus 5
- Listed as
- Claude Opus 5
- Conditions
- Max · proximus
- Unit
- mean@5
- Model released
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · FrontierSWE results, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #8 of 23 matched modelsMax · proximusModel released Jul 24, 2026Source: frontierswe.com (opens in a new tab) - WebDev ArenaWeb development · LMArena1,689
WebDev Arena: 1,689
- Model
- Claude Opus 5
- Listed as
- Claude Opus 5 (Max)
- Conditions
- Max
- Interval
- 1683–1695
- Unit
- Arena score
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Best of 2 reported results for this model.
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
Show 1 more result with other run conditionsHide the other results
- Listed as Claude Opus 5 (High)1,659
WebDev Arena: 1,659
- Model
- Claude Opus 5
- Listed as
- Claude Opus 5 (High)
- Conditions
- High
- Interval
- 1653–1664
- Unit
- Arena score
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
- Agent ArenaAgents · LMArena+0.08
Agent Arena: +0.08
- Model
- Claude Opus 5
- Listed as
- Claude Opus 5 (Max)
- Conditions
- Max · Arena Agent Mode
- Interval
- 0.06 to 0.10
- Unit
- net improvement
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
Rank #9 of 48 matched modelsMax · Arena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab) - GPQA DiamondReasoning · Epoch AI93.9%
GPQA Diamond: 93.9%
- Model
- Claude Opus 5
- Listed as
- claude-opus-5_max
- Conditions
- Max
- Unit
- % correct
- Run date
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Best of 3 reported results for this model.
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 96.5%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.
Show 2 more results with other run conditionsHide the other results
- Listed as claude-opus-592.9%
GPQA Diamond: 92.9%
- Model
- Claude Opus 5
- Listed as
- claude-opus-5
- Conditions
- Not reported
- Unit
- % correct
- Run date
- Aug 6, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as claude-opus-5_low87.9%
GPQA Diamond: 87.9%
- Model
- Claude Opus 5
- Listed as
- claude-opus-5_low
- Conditions
- Low
- Unit
- % correct
- Run date
- Aug 6, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI85.6%
FrontierMath Tiers 1–3 (v2): 85.6%
- Model
- Claude Opus 5
- Listed as
- claude-opus-5_max
- Conditions
- Max
- Unit
- % solved
- Run date
- Jul 24, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 95.1%, and Epoch AI estimates the reachable maximum at 95%. Differences between top models are small.
- SimpleQA VerifiedKnowledge · Epoch AI59.9%
SimpleQA Verified: 59.9%
- Model
- Claude Opus 5
- Listed as
- claude-opus-5_max
- Conditions
- Max
- Unit
- % correct
- Run date
- Aug 10, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Pricing
List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. Anthropic is the lab's own API and the reference price for the estimates below.
Price at real agent usageEstimate at list prices
What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.
- At this model's mix
- $0.85
- Est. per 1M tokens
95% cache reads - At the community mix
- $0.76
- Est. per 1M tokens
96% cache reads - 3:1 input/output blend
- $10
- Per 1M tokens at list prices
No cache
Cache reads were 95% of Claude Opus 5 tokens in the last 7 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.
Assumptions
- Anthropic list prices per 1M tokens: input $5, output $25, cache read $0.50, cache write $6.25.
- This model's mix is its own input, output, cache and reasoning tokens in the last 7 days.
- The community mix is the tokens of every identified model in the last 7 days.
- This is an estimate at list prices, not what anyone paid.
- Reasoning tokens are priced as output.
- Long-context tiers, batch pricing and discounts are not applied.
- Token mixes come from public Tokscale submissions. Hidden accounts are excluded.
List prices by provider
- AnthropicReference
claude-opus-5$5 input per 1M tokens$25 output per 1M tokens$0.50 cache read per 1M tokens$6.25 cache write per 1M tokens1M tokens of context - Amazon Bedrock
anthropic.claude-opus-5$5 input per 1M tokens$25 output per 1M tokens$0.50 cache read per 1M tokens$6.25 cache write per 1M tokens1M tokens of context - Vertex
claude-opus-5@default$5 input per 1M tokens$25 output per 1M tokens$0.50 cache read per 1M tokens$6.25 cache write per 1M tokens1M tokens of context - Vertex (Anthropic)
claude-opus-5@default$5 input per 1M tokens$25 output per 1M tokens$0.50 cache read per 1M tokens$6.25 cache write per 1M tokens1M tokens of context
Show 3 more providersShow fewer providers
- Azure
claude-opus-5$5 input per 1M tokens$25 output per 1M tokens$0.50 cache read per 1M tokens$6.25 cache write per 1M tokens1M tokens of context - OpenRouter
anthropic/claude-opus-5$5 input per 1M tokens$25 output per 1M tokens$0.50 cache read per 1M tokens$6.25 cache write per 1M tokens1M tokens of context - Vercel AI Gateway
anthropic/claude-opus-5$5 input per 1M tokens$25 output per 1M tokens$0.50 cache read per 1M tokens$6.25 cache write per 1M tokens1M tokens of context
Specs
From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.
- Context window
- 1M tokens
- Max output
- 128K tokens
- Input
- Text, Image, PDF
- Output
- Text
- Knowledge cutoff
- May 2026
- Release date
- Jul 24, 2026
- Open weights
- No
- Reasoning
- Yes
- Tool calling
- Yes
Top public profiles
Public profiles that used Claude Opus 5 most in this period, by tokens. Hidden accounts are never listed.
- 1
Shad0w23333@Shad0w233335.3Btokens$3.7Kest. cost6active days$3.7K est. cost · 6 active days
- 2
DayLab@daylab-official3.5Btokens$3Kest. cost6active days$3K est. cost · 6 active days
- 3
yunwang6131@yunwang61312.1Btokens$1.3Kest. cost6active days$1.3K est. cost · 6 active days
- 4
Wooseok Sung@MercuriusDream1.2Btokens$1.2Kest. cost3active days$1.2K est. cost · 3 active days
- 5
nkhosla@nkhosla944.2Mtokens$650est. cost4active days$650 est. cost · 4 active days
- 6
YeonGyu-Kim@code-yeongyu853.4Mtokens$965est. cost4active days$965 est. cost · 4 active days
- 7
potato dog man@saumilthecode733.1Mtokens$484est. cost2active days$484 est. cost · 2 active days
- 8
ToToKr@MoerAI580.3Mtokens$500est. cost7active days$500 est. cost · 7 active days
- 9
Ing Tian@IngTian553Mtokens$442est. cost3active days$442 est. cost · 3 active days
- 10
Perth@Perthys394.1Mtokens$301est. cost1active days$301 est. cost · 1 active days
More from Anthropic
Other Anthropic models in the same period, by active users.
- Claude Opus 5.571% adoption434active users
- Claude Sonnet 5.545% adoption277active users
- Claude Haiku 5.541% adoption249active users
- Claude Fable 5.232% adoption196active users
- Claude Fable 5.125% adoption154active users
- Claude Opus 4.87.7% adoption47active users
Sources and attribution
Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.