BenchLeader

Claude Haiku 4.5

Reasoning effort

Claude Haiku 4.5 is an Anthropic proprietary reasoning model, released 15 Oct 2025. Its best configuration (no reasoning reasoning effort) ranks #424 of 785 on the BenchLeader Index at 48.5 ±5.4, in the lower half. The ± is the point: 349 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in knowledge (58) and lowest in multimodal (38). At $2.00 per million tokens blended it is pricier than most ranked models. Output speed of 84 tokens per second puts it slower than most, with a first answer in 0.5 s. It has been measured at 5 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 15 Oct 2025.stale: no new result in six months

Blended price
$2.00/M
$1.00 in · $5.00 out
Output speed
84 tok/s
measured by Artificial Analysis
First answer
0.48 s
first token 0.48 s
Context
200k
Full answer
6.46 s
median, reasoning included
Cost per run
–
Released
15 Oct 2025
How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.
  1. Overall index49
  2. Reasoning41
  3. Agents & tools58
  4. Knowledge58
  5. Instruction following45
  6. Multimodal38
  7. Long context49
  8. Composite47

Versions

Anthropic has shipped 6 models under this name. Each is ranked on its own results; a newer version often has fewer results so far, which holds its index nearer the average until more arrive.

ModelReleasedIndexRank
Claude Haiku 5.5xhigh7 Oct 202661.5#95
Claude Haiku 4.5no reasoningthis page15 Oct 202548.5#424
Claude 3.5 Haiku4 Nov 202439.7#675
Claude 3 Haiku7 Mar 202437.0#738
Claude Haiku 3–––
Claude Haiku 4thinking–––

Reasoning-effort configurations

The same model behaves differently depending on how much it is allowed to think. Each row is one setting, scored only on the benchmarks that were run at that setting. “Not stated” collects results from publishers that did not say which setting they used; for a reasoning model that is usually its thinking mode, but we do not assume it. Pick a setting here or at the top of the page to see its price, speed and category scores.

EffortIndexRankSpeedFirst answerChat reply costCategories
no reasoningbest48.5#42484 tok/s0.48 s$0.0019Agents & tools 58 · Composite 47 · Instruction following 45 · Knowledge 58 · Long context 49 · Multimodal 38 · Reasoning 41
low––63 tok/s0.87 s$0.0019
high––63 tok/s0.87 s$0.0019Coding 59
thinking46.7#47694 tok/s19 s$0.0019Agents & tools 41 · Coding 27 · Composite 48 · Instruction following 47 · Knowledge 52 · Long context 62 · Maths 58 · Multimodal 41 · Reasoning 39
not stated45.3#51663 tok/s0.87 s$0.0019Agents & tools 45 · Coding 48 · Composite 26 · Human preference 49 · Instruction following 52 · Knowledge 35 · Maths 61 · Reasoning 43

How its index has moved

8 Sept 2026 to 25 Oct 2026
404856
  • no reasoning
  • thinking
  • not stated

The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.

Benchmark results

See all LLM benchmarks. One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.

Reasoning

Benchmarkno reasoningthinkingnot statedSourceTrend
GPQA Diamondeffort not stated––71.2%#168Epoch AI Benchmarking Hub
Arena Hard Promptseffort not stated––1442#121Arena (LMArena)
LiveBench 2.0 Reasoningnot in indexeffort not stated––61.7%#51LiveBench
GPQA Diamond (AA)not in index64.7%#34567.2%#322–Artificial Analysis
Humanity's Last Exam (AA)not in index4.2%#52210.4%#318–Artificial Analysis
GPQA Diamond (Vals)not in index–72.2%#84–Vals AI
GPQA Diamond (HELM)not in indexeffort not stated––60.5%#27HELM Capabilities
ARC-AGI-1–47.7%#18314.3%#229ARC Prize
ARC-AGI-2–4.0%#1851.3%#218ARC Prize
CritPt0.0%#3150.0%#315–Artificial Analysis
Chess Puzzlesnot in indexeffort not stated––8.0%#124Epoch AI Benchmarking Hub
LMCAnot in indexeffort not stated––30.9%#134Epoch AI Benchmarking Hub
DTBenchnot in indexeffort not stated––73.6%#153Epoch AI Benchmarking Hub
ForecastBenchnot in indexeffort not stated––63.4%#40ForecastBench

Coding

Benchmarkhighthinkingnot statedSourceTrend
SciCodeeffort not stated––42.3%#150SciCode
WeirdMLeffort not stated––45.4%#85WeirdML
Arena Codingeffort not stated––1482#104Arena (LMArena)
Arena WebDeveffort not stated––1331#116Arena (LMArena)
LiveBench 2.0 Codingnot in indexeffort not stated––48.1%#49LiveBench
SciCode (AA)not in index–42.3%#161–Artificial Analysis
LiveCodeBench–41.2%#124–Vals AI
SWE-bench (Vals)not in index–66.6%#68–Vals AI
SWE-Bench Proeffort not stated––39.5%#12Scale AI SEAL
SWE-bench Verified (bash only)66.6%#16––SWE-bench
SWE-bench Verified (any scaffold)not in index66.6%#17––SWE-bench
Code Migrationnot in index–7.5%#63–Vals AI
ProgramBenchnot in index–0.0%#32–Vals AI
Vibe Code Bench v1.1not in index–11.4%#97–Vals AI
SWE-Bench Pro (private)not in indexeffort not stated––39.5%#12Scale AI SEAL
ALE-Benchnot in indexeffort not stated––653.5#92Epoch AI Benchmarking Hub
Terminal-Bench 4.0 (AA)not in index–0.0%#152–Artificial Analysis
Terminal-Bench 2.1 (AA)not in index–44.2%#130–Artificial Analysis
Startrise Frontendnot in indexeffort not stated––44.8%#29Startrise

Agents & tools

Benchmarkno reasoninglowthinkingnot statedSourceTrend
Terminal-Bencheffort not stated–––35.5%#54Terminal-Bench
LiveBench Long Agenticnot in indexeffort not stated–––11.1%#51LiveBench
LiveBench Browsernot in indexeffort not stated–––40.0%#34LiveBench
Terminal-Bench Hard27.3%#125–27.3%#125–Artificial Analysis
τ²-Bench Telecom (AA)not in index32.5%#247–54.7%#186–Artificial Analysis
Terminal-Bench 2.1 (Vals)––43.8%#63–Vals AI
MCP Atlaseffort not stated–––40.2%#33Scale AI SEAL
BFCL Overalleffort not stated–––68.7%#6Berkeley Function Calling Leaderboard
τ³-Banking (AA)––9.3%#150–Artificial Analysis
ITBench SRE (AA)not in index––27.3%#35–Artificial Analysis
Analyst Agent (AA)not in index––15.0%#41–Artificial Analysis
Finance Agent v2not in index––31.0%#68–Vals AI
Harvey's Legal Agent Benchmark v1not in index––0.8%#56–Vals AI
Legal Research Benchnot in index––10.6%#72–Vals AI
Tax Agent Benchnot in index––5.9%#67–Vals AI
Terminal-Bench 2.0 (Vals)not in index––38.2%#36–Vals AI
BALROGnot in indexeffort not stated–––31.2%#17BALROG
DeepResearch Benchnot in index–45.5%#29––DeepResearch Bench
ExploitBenchnot in indexeffort not stated–––13.7%#8Epoch AI Benchmarking Hub
Vending-Bench 2not in indexeffort not stated–––458.9#60Andon Labs
AutomationBenchnot in index––3.3%#172–Artificial Analysis
GDP.pdf (AA)not in index––3.8%#173–Artificial Analysis
EnterpriseOps-Gymnot in index––29.4%#41–Artificial Analysis
DeepSearchQAnot in index––12.8%#12–Google

Maths

Benchmarkthinkingnot statedSourceTrend
OTIS Mock AIMEeffort not stated–66.7%#149Epoch AI Benchmarking Hub
MATH Level 5effort not stated–96.4%#11Epoch AI Benchmarking Hub
AIME (Vals)82.7%#44–Vals AI
MGSM92.2%#21–Vals AI
Omni-MATH (HELM)effort not stated–56.1%#12HELM Capabilities
Arena Mathseffort not stated–1402#147Arena (LMArena)

Knowledge

Benchmarkno reasoningthinkingnot statedSourceTrend
SimpleQA Verifiedeffort not stated––13.2%#80Epoch AI Benchmarking Hub
LiveBench 2.0 Data Analysisnot in indexeffort not stated––59.3%#47LiveBench
LiveBench Researchnot in indexeffort not stated––42.2%#50LiveBench
AA-Omniscience-7.6#176-4.4#159–Artificial Analysis
MMLU-Pro–78.7%#95–Vals AI
LegalBench–81.2%#81–Vals AI
CorpFin–60.6%#6660.3%#69Vals AI
TaxEval–67.5%#102–Vals AI
MedQA–79.6%#70–Vals AI
MMLU-Pro (HELM)not in indexeffort not stated––77.7%#27HELM Capabilities
CaseLaw v2not in index–56.5%#30–Vals AI
Excel Modeling Benchmarknot in index–22.7%#67–Vals AI
MedCodenot in index–32.7%#85–Vals AI
MedScribenot in index–85.2%#30–Vals AI
Public Benefits Bench v1.1not in indexeffort not stated––54.3%#40Vals AI
AA-Omniscience: accuracynot in index14.4%#43618.0%#346–Artificial Analysis
AA-Omniscience: non-hallucinationnot in index74.3%#2672.7%#33–Artificial Analysis

Instruction following

Benchmarkno reasoningthinkingnot statedSourceTrend
IFBench42.0%#23954.3%#154–Artificial Analysis
MultiChallenge–50.5%#27–Scale AI SEAL
IFEval (HELM)effort not stated––80.1%#48HELM Capabilities
WildBench (HELM)effort not stated––83.9%#15HELM Capabilities
Arena Instruction Followingnot in indexeffort not stated––1415#114Arena (LMArena)

Human preference

Benchmarknot statedSourceTrend
Arena Text1415#133Arena (LMArena)
EQ-Bench 41057#28EQ-Bench
Arena Creative Writingnot in index1387#126Arena (LMArena)
Arena Multi-turnnot in index1425#118Arena (LMArena)
Arena Longer Queriesnot in index1437#110Arena (LMArena)

Multimodal

Benchmarkno reasoningthinkingnot statedSourceTrend
LiveBench Designnot in indexeffort not stated––59.9%#48LiveBench
MMMU-Pro55.1%#22858.5%#217–Artificial Analysis
MMMU-Pro (Vals)not in index–46.1%#88–Vals AI
MortgageTaxnot in index–62.2%#54–Vals AI
SAGEnot in index–31.8%#74–Vals AI
Blueprint-Bench 2not in indexeffort not stated––0.0%#29Epoch AI Benchmarking Hub

Long context

Benchmarkno reasoningthinkingnot statedSourceTrend
AA-LCR49.7%#32574.3%#162–Artificial Analysis
Arena Documentnot in indexeffort not stated––1419#42Arena (LMArena)
MLCRnot in index–5.0%#145–Artificial Analysis

Composite

Benchmarkno reasoningthinkingnot statedSourceTrend
Epoch Capabilities Indexnot in indexeffort not stated––142.2#103Epoch AI Benchmarking Hub
LiveBench 2.0effort not stated––46.0%#49LiveBench
AA Intelligence Index v4.3.215.4#28316.9#267–Artificial Analysis
HELM Capabilities meannot in indexeffort not stated––71.7%#22HELM Capabilities
Vals Multimodal Indexnot in index–42.9%#28–Vals AI

Where to run it

Every provider serving this model through OpenRouter, with throughput and first-token latency measured on live traffic over the last 30 minutes and each provider’s own price. Purple marks the best in each column.

ProviderSpeedFirst tokenInput $/MOutput $/MContextQuantisation
Google Vertex153 tok/s2.58 s$1.10$5.50200k–
Amazon Bedrock130 tok/s0.65 s$1.10$5.50200k–
Amazon Bedrock112 tok/s0.56 s$1.10$5.50200k–
Google Vertex104 tok/s0.57 s$1.10$5.50200k–
Google Vertex91 tok/s0.69 s$1.00$5.00200k–
Azure79 tok/s0.44 s$1.00$5.00200k–
Anthropic67 tok/s0.44 s$1.00$5.00200k–
Amazon Bedrock60 tok/s0.81 s$1.00$5.00200k–

What a task costs

Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache at $0.100 per 1M. Reasoning tokens are not modelled.

WorkloadTokens in / outCostWith cachingTime
Chat reply400 / 300$0.0019$0.00164.1 s
Summarize a 30-page report12,000 / 600$0.015$0.00697.7 s
Code edit6,000 / 1,500$0.013$0.009518.4 s
Agentic coding session60,000 / 4,000$0.080$0.04048.3 s
Structured extraction2,000 / 200$0.0030$0.00172.9 s

More from Anthropic

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See also

Questions people ask

What are Claude Haiku 4.5's benchmark scores?
As of 25 Oct 2026, Claude Haiku 4.5 (no reasoning effort) scores 48.5 ±5.4 on the BenchLeader Index, strongest in knowledge (58) and weakest in multimodal (38). That rests on 7 independent benchmark results, and every score on this page links to its publisher.
How does Claude Haiku 4.5 rank?
Claude Haiku 4.5 (no reasoning effort) is #424 of 785 ranked configurations on 25 Oct 2026. 349 other configurations score within its margin, so the exact position matters less than the band. The leader is Claude Opus 5.5 (max effort) at 72.6.
How much does Claude Haiku 4.5 cost per 1M tokens?
As of 25 Oct 2026, Claude Haiku 4.5 costs $1.00 per 1M input tokens and $5.00 per 1M output tokens, $2.00 blended (three input tokens per output token).
When was Claude Haiku 4.5 released?
Anthropic released Claude Haiku 4.5 on 15 Oct 2025. BenchLeader has results for it at 5 reasoning-effort settings.

Data as of 25 Oct 2026. Compare these configurations.

Cite as: BenchLeader, “Claude Haiku 4.5: benchmarks, pricing, speed and rank”, data as of 25 Oct 2026, https://www.benchleader.com/models/claude-haiku-4-5.