Qwen3Guard Gen 0.6B
chutes/qwen3guard-gen-0-6bمن chutes · العائلة: qwen · أُصدِر 2025-12-29
⚠ هذا نموذج مُحسَّن من المجتمع أو مشتق — وليس إصدارًا رسميًا من المزود.
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
القدرات
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding1
- Tool calling0/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)0/20
- Provider availability1/10
Agents6
- Tool calling0/35
- Structured output0/25
- Reasoning0/15
- Output token limit5/15
- Provider availability1/10
JSON / structured output30
- Structured output / JSON mode0/50
- Tool calling0/20
- Temperature control10/10
- Price-friendly for high-volume20/20
Cost efficiency100
- Headline price (log-scaled)95/95
- Has prompt-cache pricing5/5
Long context0
- Context ≥ 100K0/100
Production-readiness50
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers10/10
- Official model (not derivative)0/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.06 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $0.11 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $0.03 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $0.09 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $0.13 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
تفاصيل التسعير
السعر المُوصى به من chutes · Qwen/Qwen3Guard-Gen-0.6B
متاح لدى 1 مزود
| المزود | معرف نموذج المزود | إدخال / 1M | إخراج / 1M | السياق | تاريخ الإصدار |
|---|---|---|---|---|---|
| Chutes chutes | Qwen/Qwen3Guard-Gen-0.6B | $0.010 | $0.011 | 33K | 2025-12-29 |
Frequently asked questions
How much does Qwen3Guard Gen 0.6B cost?
Qwen3Guard Gen 0.6B costs $0.010 per 1M input tokens and $0.011 per 1M output tokens, sourced from chutes. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Qwen3Guard Gen 0.6B?
Qwen3Guard Gen 0.6B has a context window of 33K tokens, with a max output of 8K tokens per reply. This is the total combined size of prompt + completion.
Does Qwen3Guard Gen 0.6B support tool calling?
No. Qwen3Guard Gen 0.6B does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does Qwen3Guard Gen 0.6B support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Qwen3Guard Gen 0.6B in our data source. Verify with chutes's official documentation before relying on it in production.
Can Qwen3Guard Gen 0.6B accept image input?
No. Qwen3Guard Gen 0.6B only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Qwen3Guard Gen 0.6B open-weight?
Yes. Qwen3Guard Gen 0.6B's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.
What are the best alternatives to Qwen3Guard Gen 0.6B?
If Qwen3Guard Gen 0.6B doesn't fit, consider Hermes 4 14B, MiMo V2 Flash TEE, dots.ocr. Each one targets the same use case — see the Related links below for direct head-to-head pages.
Where does this data come from?
All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More chutes models
- Hermes 4 14B$0.01 in / $0.05 out
- MiMo V2 Flash TEE$0.09 in / $0.29 out
- dots.ocr$0.01 in / $0.01 out
Capability lists this model is in
آخر تحديث:
Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.