v0-1.5-lg
v0/v0-1-5-lgBy v0 · family: v0 · released 2025-06-09
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.
Coding65
- Tool calling40/40
- Structured output0/20
- Reasoning10/10
- Context window (100K → 1M)14/20
- Provider availability1/10
Agents66
- Tool calling35/35
- Structured output0/25
- Reasoning15/15
- Output token limit15/15
- Provider availability1/10
JSON / structured output30
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume0/20
Cost efficiency14
- Headline price (log-scaled)14/95
- Has prompt-cache pricing0/5
Long context75
- Context window (100K → 2M)65/90
- Has published price for full window10/10
Vision87
- Accepts image input50/50
- Context window (10K → 1M)26/30
- 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 | $113 $0.11 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 | $225 $0.02 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 | $67.50 $0.07 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 | $195 $0.20 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $225 $0.23 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 v0 · v0-1.5-lg
Available on 1 providers
| Provider | Provider model id | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|---|
| v0 v0 | v0-1.5-lg | $15.00 | $75.00 | 512K | 2025-06-09 |
Frequently asked questions
How much does v0-1.5-lg cost?
v0-1.5-lg costs $15.00 per 1M input tokens and $75.00 per 1M output tokens, sourced from v0. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of v0-1.5-lg?
v0-1.5-lg has a context window of 512K tokens, with a max output of 32K tokens per reply. This is the total combined size of prompt + completion.
Does v0-1.5-lg support tool calling?
Yes. v0-1.5-lg 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 v0-1.5-lg support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for v0-1.5-lg in our data source. Verify with v0's official documentation before relying on it in production.
Can v0-1.5-lg accept image input?
Yes. v0-1.5-lg accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check v0's docs for the exact rule.
Is v0-1.5-lg open-weight?
No. v0-1.5-lg is a proprietary model — only v0 (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to v0-1.5-lg?
If v0-1.5-lg doesn't fit, consider v0-1.0-md, v0-1.5-md. 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.
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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.