LangMart: Qwen: Qwen3 8B
Model Overview
| Property | Value |
|---|---|
| Model ID | openrouter/qwen/qwen3-8b |
| Name | Qwen: Qwen3 8B |
| Provider | qwen |
| Released | 2025-04-28 |
Description
Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between "thinking" mode for math, coding, and logical inference, and "non-thinking" mode for general conversation. The model is fine-tuned for instruction-following, agent integration, creative writing, and multilingual use across 100+ languages and dialects. It natively supports a 32K token context window and can extend to 131K tokens with YaRN scaling.
Description
LangMart: Qwen: Qwen3 8B is a language model provided by qwen. This model offers advanced capabilities for natural language processing tasks.
Provider
qwen
Specifications
| Spec | Value |
|---|---|
| Context Window | 128,000 tokens |
| Modalities | text->text |
| Input Modalities | text |
| Output Modalities | text |
Pricing
| Type | Price |
|---|---|
| Input | $0.03 per 1M tokens |
| Output | $0.11 per 1M tokens |
Capabilities
- Frequency penalty
- Include reasoning
- Logit bias
- Logprobs
- Max tokens
- Presence penalty
- Reasoning
- Repetition penalty
- Response format
- Seed
- Stop
- Structured outputs
- Temperature
- Tool choice
- Tools
- Top k
- Top logprobs
- Top p
Detailed Analysis
Qwen3-8B is a mid-compact model in the Qwen 3 series, offering strong general-purpose capabilities with efficient inference. Released April 2025. Key characteristics: (1) Architecture: 8B parameter dense transformer achieving performance comparable to Qwen2.5-14B through enhanced architecture and 36T token training (vs 18T for Qwen 2.5); includes Qwen 3 improvements in attention, positional encoding, and multi-step reasoning; (2) Performance: Competitive with much larger Qwen 2.5 models and commercial models like GPT-3.5-Turbo on most tasks; strong performance on reasoning, coding, and long-context understanding; (3) Use Cases: Production deployments requiring balance of capability and cost, general-purpose AI applications, code assistance, content generation, conversational AI, multi-turn dialogue systems, document analysis; (4) Context Window: 131K tokens enabling comprehensive document processing; (5) Pricing: Paid tier with cost-effective pricing reflecting efficient 8B size; (6) Trade-offs: Excellent balance point in the Qwen 3 lineup - significantly more capable than 4B model while maintaining efficient inference. Best for production applications where Qwen3-4B is insufficient but full 32B/235B scale is overkill. The sweet spot for many general-purpose deployments.