qwen3.5-4bRunware Inc.
- api
- chat
- hosting
- UK
- model lab
- Qwen
- weights
- open
- added
- March 2026
- model id
- runware/qwen3.5-4b
capabilities 4/8
- input
- $0.05
- output
- $0.07
- cache write
- -
- cache read
- $0.0050
worked cost
| volume | cost |
|---|---|
| 100K in + 10K out | $0.0057 |
| 1M in + 100K out | $0.0570 |
| 10M in + 1M out | $0.57 |
Requesty charges what the upstream provider charges, with no markup and no per-request fee. Prompt caching and smart routing cut the effective cost further on repeated context. Gateway pricing
no measured traffic for this endpoint yet. pricing above is the provider's own
| eval | Score as a share of 100 | /100 |
|---|---|---|
| τ²-Bench | 92.1 | |
| GPQA Diamond | 77.1 | |
| Coding Index | 22.6 | |
| Terminal-Bench Hard | 18.2 | |
| Intelligence Index | 13.1 | |
| Humanity's Last Exam | 9.9 | |
| 6 evals | mean | 38.8 |
Scores from Artificial Analysis and public leaderboards, normalised to 100. Bar colour is the band, not the rank: green 80 and up, blue 55 and up, amber 30 and up. Benchmarks measure narrow skills, so test on your own workload before committing. Released 2026-03-02.
- retention
- none
- trains on prompts
- no
- hosted in
- UK
Terms are the provider's, not Requesty's: routing a request here puts it under them. Runware Privacy Policy
Need every request to stay in one jurisdiction? EU hosting routes only through EU-hosted providers.
runware/qwen3.5-4bthis id pins the runware inc. deployment, with no routing and no failover. the managed id on the canonical page routes across all 1 providers instead
from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create( model="runware/qwen3.5-4b", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ],) print(response.choices[0].message.content)
Change the base url to https://router.requesty.ai/v1, use your Requesty key, set the model to the id above. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog. Browse all models
Qwen3.5 4B is a lightweight hybrid-reasoning model from the Qwen3.5 family, optimized for high-throughput, cost-sensitive workloads with a 262K token context window, tool calling, and structured output support. Served via Runware.
questions 6
How much does qwen3.5-4b cost?
What is the context window of qwen3.5-4b?
How does qwen3.5-4b perform on benchmarks?
What can qwen3.5-4b do?
How do I use qwen3.5-4b with the OpenAI SDK?
Can I run qwen3.5-4b through Requesty?
more from runware inc. 6
| endpoint | ctx | in /M |
|---|---|---|
| glm-5.3-flash | 1.0M | $0.07 |
| glm-5.3 | 1.0M | $1.20 |
| deepseek-v4-flash-0731 | 1.0M | $0.08 |
| glm-5.2 | 1.0M | $0.80 |
| qwen3.5-9b | 262K | $0.09 |
| gpt-oss-120b | 131K | $0.03 |
call qwen3.5-4b through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover when a provider degrades, and prompt caching built in. Methodology
