Qwen 3.5 35B A3B
Qwen 3.5 35B A3B is an open-weight, multimodal reasoning model from Alibaba with strong vision, code, and agent capabilities at aggressive pricing.
Overview
What is Qwen 3.5 35B A3B
Qwen 3.5 35B A3B is a 35-billion-parameter multimodal language model from Alibaba, released in February 2026. It supports text, image, and video input with text output, excelling in reasoning, coding, and agentic workflows. Built with a hybrid sparse MoE architecture, it delivers high throughput and cost efficiency.
Running it privately on Venice
On Venice, Qwen 3.5 35B A3B runs with zero retention — your prompts are never stored or profiled. This open-weight model operates under full user sovereignty, enabling private, uncensored access to a high-performance vision-language model without Big Tech surveillance. Use it for code, agents, or vision tasks with end-to-end privacy.
Assessment
Strengths and limitations
- Open weights with permissive Apache 2.0 license: inspectable, modifiable, and self-hostable.
- Strong multimodal reasoning: integrates vision and text natively for robust visual understanding and coding tasks.
- Highly cost-efficient for input tokens, making it ideal for long-context RAG and document processing.
- Supports tool calling, web search, and structured JSON output for agent workflows.
- Efficient hybrid architecture enables fast inference with low latency overhead.
- Output token pricing is relatively high compared to some rivals, impacting long-generation tasks.
- Not the strongest performer in general knowledge or multilingual tasks outside core benchmarks.
- Closed reasoning path: while weights are open, training data and full pipeline details are not fully public.
Capabilities
What it supports
- Tool use / function calling
- Vision (image input)
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Audio input
- Video input
- Multiple image inputs
- Log probabilities
Specifications
Datasheet
- Maker
- Alibaba
- Released
- February 2026
- Architecture
- Hybrid MoE with linear attention
- Parameters
- 35B
- Open weights
- Yes — Apache 2.0
- Context window
- 256K tokens
- Max output
- 16.384K tokens
- Capabilities
- Vision, Function calling, Reasoning, Web search, Code-optimized
- Privacy on Venice
- Private — zero retention
- Available on Venice since
- Feb 2026
- License
- Apache 2.0
API
Call it from your code
Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-5-35b-a3b",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $0.31 per 1M input tokens and $1.25 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Alternatives
How it compares
| Model | Max resolution | Strongest at | Open weights | Price (Venice) |
|---|---|---|---|---|
| Qwen 3.5 35B A3B | Multiple images, video | Vision, code, agentic tasks | Yes | $0.31 in · $1.25 out / 1M |
| DeepSeek V4 Flash 0731 | Image input | Speed, low-cost inference | No | $0.17 in · $0.35 out / 1M |
| Google Gemma 4 31B Instruct | Image input | Balanced reasoning, multilingual | Yes | $0.12 in · $0.36 out / 1M |
| GLM 5.1 | Image input | Chinese NLP, enterprise RAG | Yes | $1.10 in · $4.15 out / 1M |
Open, private, and vision-capable with strong agentic performance.
Use cases
What it is good for
- 01Private AI agents that require vision, code generation, and tool use without data retention.
- 02Long-context retrieval-augmented generation (RAG) with multimodal inputs.
- 03Code repair, repository-level reasoning, and software engineering workflows.
- 04Vision-based classification and document understanding in regulated or sensitive environments.
- 05Cost-sensitive production deployments where open weights and privacy are mandatory.
Prompting
Getting better results
Use structured outputs with JSON schema when you need predictable, machine-readable responses.
Enable web search for real-time data; combine with vision for multimodal retrieval.
Leverage function calling to connect to internal tools or APIs securely without exposing prompts.
For long documents, use caching to reduce cost and latency on repeated prefixes.
Version history
Predecessor model with similar architecture
Current — enhanced vision and reasoning
Successor with improved stability and coding
FAQ
Frequently asked questions
Qwen 3.5 35B A3B is a 35-billion-parameter multimodal language model developed by Alibaba. It supports text, image, and video input with strong reasoning, coding, and agent capabilities, released in February 2026 under the Apache 2.0 license.
No, Qwen 3.5 35B A3B is not free — it is billed per token on Venice at $0.31 per 1M input tokens and $1.25 per 1M output tokens. However, its open weights allow self-hosting for free if you run it independently.
Yes, Qwen 3.5 35B A3B is open weights under the permissive Apache 2.0 license. You can inspect, modify, and self-host the model, though training data and pipeline details are not fully public.
Qwen 3.5 35B A3B has a context window of 256K tokens, allowing it to process very long documents, codebases, or multimodal sequences in a single pass.
Yes, Qwen 3.5 35B A3B supports image and video input natively, enabling visual reasoning, document understanding, and multimodal tasks without requiring external processors.
Yes, Qwen 3.5 35B A3B supports function calling and tool use, allowing it to interact with external APIs, databases, or internal systems as part of agent workflows.
Qwen 3.5 35B A3B is stronger in vision and multimodal reasoning, while DeepSeek V4 Flash 0731 is faster and cheaper per token. Choose Qwen for agentic vision tasks with privacy; choose DeepSeek for low-cost, high-speed inference on text-only workloads.
Yes, Qwen 3.5 35B A3B supports structured outputs using JSON schema, making it reliable for API integrations and applications requiring predictable data formats.
Run Qwen 3.5 35B A3B privately
No prompt logging. No data used for training.