Ornith 1.5 35B A3B
runinfra/ornith-1-5-35b-a3bBy runinfra · family: ornith · released 2026-08-18
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capabilities
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.
Coding79
- Tool calling40/40
- Structured output20/20
- Reasoning10/10
- Context window (100K → 1M)8/20
- Provider availability1/10
Agents91
- Tool calling35/35
- Structured output25/25
- Reasoning15/15
- Output token limit15/15
- Provider availability1/10
JSON / structured output99
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume19/20
Cost efficiency75
- Headline price (log-scaled)70/95
- Has prompt-cache pricing5/5
Long context61
- Context window (100K → 2M)51/90
- Has published price for full window10/10
Vision82
- Accepts image input50/50
- Context window (10K → 1M)21/30
- Has published price10/10
- Provider availability1/10
Production-readiness65
- 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)15/15
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 | $0.70 < $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 | $1.40 < $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 | $0.40 < $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 | $1.20 < $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 | $1.44 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Pricing detail
Recommended pricing from runinfra · ornith-ai/Ornith-1.5-35B-A3B
Available on 1 providers
| Provider | Provider model id | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|---|
| RunInfra runinfra | ornith-ai/Ornith-1.5-35B-A3B | $0.100 | $0.400 | 262K | 2026-08-18 |
Frequently asked questions
How much does Ornith 1.5 35B A3B cost?
Ornith 1.5 35B A3B costs $0.100 per 1M input tokens and $0.400 per 1M output tokens, sourced from runinfra. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Ornith 1.5 35B A3B?
Ornith 1.5 35B A3B has a context window of 262K tokens, with a max output of 33K tokens per reply. This is the total combined size of prompt + completion.
Does Ornith 1.5 35B A3B support tool calling?
Yes. Ornith 1.5 35B A3B supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does Ornith 1.5 35B A3B support structured output / JSON mode?
Yes. Ornith 1.5 35B A3B supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Can Ornith 1.5 35B A3B accept image input?
Yes. Ornith 1.5 35B A3B accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check runinfra's docs for the exact rule.
Is Ornith 1.5 35B A3B open-weight?
Yes. Ornith 1.5 35B A3B'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.
Where does this data come from?
All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
Last updated:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.