BenchLeader

Qwen3.5-4B

Reasoning effort

Qwen3.5-4B is an Alibaba open-weights reasoning model, released 24 Feb 2026. Its best configuration (thinking reasoning effort) ranks #473 of 775 on the BenchLeader Index at 46.6 ±5.2, in the lower half. The ± is the point: 327 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 long context (56) and lowest in knowledge (35). At $0.060 per million tokens blended it is among the cheapest fifth of ranked models. Output speed of 18 tokens per second puts it in the slowest quarter, with a first answer in 114.0 s. It has been measured at 3 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 2 Mar 2026.stale: no new result in six months

Blended price
$0.060/M
$0.030 in · $0.150 out
Output speed
18 tok/s
measured by Artificial Analysis
First answer
114 s
Context
262k
Full answer
142 s
median, reasoning included
Cost per run
–
Released
24 Feb 2026
How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.
  1. Overall index47
  2. Reasoning41
  3. Agents & tools40
  4. Knowledge35
  5. Instruction following53
  6. Multimodal48
  7. Long context56
  8. Composite44

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 reasoning42.2#59213 tok/s1.06 s$0.0001Agents & tools 36 · Composite 42 · Instruction following 37 · Knowledge 28 · Long context 42 · Maths 48 · Multimodal 45 · Reasoning 41
thinkingbest46.6#47318 tok/s114 s$0.0001Agents & tools 40 · Composite 44 · Instruction following 53 · Knowledge 35 · Long context 56 · Multimodal 48 · Reasoning 41
not stated–––––Maths 31

How its index has moved

9 Sept 2026 to 19 Oct 2026
374552
  • thinking
  • no reasoning

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 reasoningthinkingSourceTrend
GPQA Diamond (AA)not in index71.2%#28577.1%#222Artificial Analysis
Humanity's Last Exam (AA)not in index8.0%#3509.9%#321Artificial Analysis
CritPt0.0%#3100.0%#310Artificial Analysis

Coding

Benchmarkno reasoningthinkingSourceTrend
Terminal-Bench 2.1 (AA)not in index21.4%#16825.8%#165Artificial Analysis

Agents & tools

Benchmarkno reasoningthinkingSourceTrend
Terminal-Bench Hard11.4%#21418.2%#170Artificial Analysis
τ²-Bench Telecom (AA)not in index87.7%#7592.1%#52Artificial Analysis
τ³-Banking (AA)4.3%#1916.8%#163Artificial Analysis

Maths

Benchmarkno reasoningnot statedSourceTrend
OTIS Mock AIME55.8%#172–Epoch AI Benchmarking Hub
AIME 2026effort not statedpossible contamination–89.7%#28MathArena
HMMT February 2026effort not statedpossible contamination–72.9%#28MathArena

Knowledge

Benchmarkno reasoningthinkingSourceTrend
AA-Omniscience-74.7#522-58.4#448Artificial Analysis
AA-Omniscience: accuracynot in index11.2%#47815.1%#415Artificial Analysis
AA-Omniscience: non-hallucinationnot in index3.2%#53813.4%#360Artificial Analysis

Instruction following

Benchmarkno reasoningthinkingSourceTrend
IFBench33.3%#32752.0%#162Artificial Analysis

Multimodal

Benchmarkno reasoningthinkingSourceTrend
MMMU-Pro62.1%#19865.4%#174Artificial Analysis

Long context

Benchmarkno reasoningthinkingSourceTrend
AA-LCR34.7%#37263.0%#265Artificial Analysis

Composite

Benchmarkno reasoningthinkingSourceTrend
AA Intelligence Index v4.3.210.8#36713.1#311Artificial Analysis

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. Reasoning tokens are not modelled.

WorkloadTokens in / outCostWith cachingTime
Chat reply400 / 300$0.0001–2.2 min
Summarize a 30-page report12,000 / 600$0.0005–2.5 min
Code edit6,000 / 1,500$0.0004–3.3 min
Agentic coding session60,000 / 4,000$0.0024–5.7 min
Structured extraction2,000 / 200$0.0001–2.1 min

More from Alibaba

New this month

See also

Data as of 21 Oct 2026. Compare these configurations.

Cite as: BenchLeader, “Qwen3.5-4B: benchmarks, pricing, speed and rank”, https://www.benchleader.com/models/qwen3-5-4b, data as of 21 Oct 2026.