score
Qwen3.5 4B (Reasoning) scores 20 (estimated) on the Artificial Analysis Intelligence Index, placing …
vs class avg: 9
Intelligence, Performance & Price Analysis
score
Qwen3.5 4B (Reasoning) scores 20 (estimated) on the Artificial Analysis Intelligence Index, placing …
vs class avg: 9
output tokens/sec
Qwen3.5 4B (Reasoning) generates output at 33.7 tokens per second (based on the median across …
TTFT
Qwen3.5 4B (Reasoning) has a time to first token (TTFT) of 0.80s (based on the median across …
/ 1M tokens
Qwen3.5 4B (Reasoning) costs $0.03 per 1M input tokens (very competitive, median: $0.18) and $0. …
/ 1M tokens
Qwen3.5 4B (Reasoning) costs $0.03 per 1M input tokens (very competitive, median: $0.18) and $0. …
Ethen's intelligence-driven routing assessment for this model
Overall verdict
Strong general-purpose model
Suitable for most production tasks, but high-volume or repetitive work should still be compared against cheaper routes.
Routing recommendation
Use the fit matrix to compare against cheaper routes when volume rises
Cost pressure
Competitive pricing — $0.03 / M input, $0.15 / M output. Cost pressure is low enough for sustained production use.
Use this model where capability pays for itself; route away where volume, latency, or budget dominate.
| Use case | Fit | Reason | Routing note |
|---|---|---|---|
| Complex reasoning & agentic workflows | Strong | Intelligence score 20 supports capable reasoning, but very hard tasks may benefit from higher-tier models. | Good for most complex tasks; consider a frontier model for the hardest 10%. |
| High-volume chat & customer-facing | Moderate | Output speed may be a bottleneck for real-time chat at scale. | Consider a faster model for latency-sensitive chat. |
| Latency-sensitive applications | Excellent | TTFT 0.80s — among the lowest latencies, suitable for interactive latency-critical use cases. | Good first choice for real-time applications. |
| Cost-sensitive pipelines | Excellent | Output pricing at $0.15 is very competitive for high-volume workloads. | Excellent for budget-constrained pipelines; enable caching to reduce costs further. |
Cost pressure
LowPricing is competitive — input $0.03, output $0.15. Suitable for sustained production use.
No cheaper substitute is supported by the current price data.
Key benchmark results at a glance.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Qwen3.5 4B (Reasoning) scores 20 (estimated) on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size (median: 9).
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Qwen3.5 4B (Reasoning) generates output at 33.7 tokens per second (based on the median across providers serving the model), which is at the lower end compared to other open weight models of similar size (median: 101.0 t/s).
Context, Cost & Pricing
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Pricing is competitive — input $0.03, output $0.15. Suitable for sustained production use.
Benchmark scores and quality indices measuring model capability.
AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Openness Index assesses model openness on a 0 to 100 normalized scale (higher is more open) · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Output tokens per second and generation throughput.
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Time to first token and end-to-end response latency.
Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Seconds to first answer token received · Accounts for reasoning model 'thinking' time · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Context window size, cost per task, and token pricing.
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Price (USD per M Tokens) · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Weighted average decode time (minutes) per task; excludes TTFT and overhead time · Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Model size, parameters, and architectural details.
Comparison between total model parameters and parameters active during inference · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
Qwen3.5 4B (Reasoning) scores 20 (estimated) on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size (median: 9). Qwen3.5 4B (Reasoning) generates output at 33.7 tokens per second (based on the median across providers serving the model), which is at the lower end compared to other open weight models of similar size (median: 101.0 t/s). Qwen3.5 4B (Reasoning) costs $0.03 per 1M input tokens (very competitive, median: $0.18) and $0.15 per 1M output tokens (very competitive, median: $0.40), based on the median across providers serving the model.
This page is rendered from the normalized profile and page JSON for Qwen3.5 4B.
Benchmark values are preserved as normalized; only layout, disclosure ordering, and typography are adjusted for readability.