Llama-3.2-90B-Vision-Instruct
meta/llama-3-2-90b-vision-instructОт Meta · семейство: llama · выпуск 2024-09-25 · дата знаний: 2023-12
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Возможности
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.
Coding48
- Tool calling40/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)2/20
- Provider availability6/10
Agents46
- Tool calling35/35
- Structured output0/25
- Reasoning0/15
- Output token limit5/15
- Provider availability6/10
JSON / structured output49
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume19/20
Cost efficiency70
- Headline price (log-scaled)65/95
- Has prompt-cache pricing5/5
Long context45
- Context window (100K → 2M)35/90
- Has published price for full window10/10
Vision83
- Accepts image input50/50
- Context window (10K → 1M)17/30
- Has published price10/10
- Provider availability6/10
Production-readiness84
- Number of independent providers30/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers4/10
- 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 | $1.95 < $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 | $3.90 < $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 | $0.90 < $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 | $3.20 < $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 | $4.44 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Детализация цен
Рекомендованная цена от io-net · meta-llama/Llama-3.2-90B-Vision-Instruct
Самый дешёвый провайдер: nvidia · Unknown вход + Unknown выход
Доступна у 6 провайдеров
| Провайдер | ID модели провайдера | Вход / 1M | Выход / 1M | Контекст | Выпуск |
|---|---|---|---|---|---|
| Azure azure | llama-3.2-90b-vision-instruct | $2.04 | $2.04 | 128K | 2024-09-25 |
| NanoGPT nano-gpt | meta-llama/llama-3.2-90b-vision-instruct | $0.901 | $0.901 | 131K | 2025-09-25 |
| IO.NET io-net | meta-llama/Llama-3.2-90B-Vision-Instruct | $0.350 | $0.400 | 16K | 2024-09-25 |
| Azure Cognitive Services azure-cognitive-services | llama-3.2-90b-vision-instruct | $2.04 | $2.04 | 128K | 2024-09-25 |
| Nvidia nvidia | meta/llama-3.2-90b-vision-instruct | Unknown | Unknown | 128K | 2024-09-25 |
| GitHub Models github-models | meta/llama-3.2-90b-vision-instruct | Unknown | Unknown | 128K | 2024-09-25 |
Расхождения данных между провайдерами
- context_window varies: 128000, 131072, 16000
- release_date varies (span 365d): 2024-09-25, 2025-09-25
- modalities varies across offerings
Провайдеры сообщают разные значения для этой модели. Сводка выше использует репрезентативного провайдера; детали — в таблице.
Frequently asked questions
How much does Llama-3.2-90B-Vision-Instruct cost?
Llama-3.2-90B-Vision-Instruct costs $0.350 per 1M input tokens and $0.400 per 1M output tokens, sourced from io-net. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Llama-3.2-90B-Vision-Instruct?
Llama-3.2-90B-Vision-Instruct has a context window of 128K tokens, with a max output of 8K tokens per reply. This is the total combined size of prompt + completion.
Does Llama-3.2-90B-Vision-Instruct support tool calling?
Yes. Llama-3.2-90B-Vision-Instruct 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 Llama-3.2-90B-Vision-Instruct support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Llama-3.2-90B-Vision-Instruct in our data source. Verify with Meta's official documentation before relying on it in production.
Can Llama-3.2-90B-Vision-Instruct accept image input?
Yes. Llama-3.2-90B-Vision-Instruct accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check Meta's docs for the exact rule.
Is Llama-3.2-90B-Vision-Instruct open-weight?
Yes. Llama-3.2-90B-Vision-Instruct'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 Llama-3.2-90B-Vision-Instruct?
If Llama-3.2-90B-Vision-Instruct doesn't fit, consider Meta-Llama-3.1-8B-Instruct, Llama-3.3-70B-Instruct, Llama 4 Maverick 17B 128E Instruct FP8. 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 Meta models
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- Llama-3.3-70B-Instruct$0.05 in / $0.23 out
- Llama 4 Maverick 17B 128E Instruct FP8$0.14 in / $0.59 out
- Llama 4 Scout 17B 16E Instruct$0.08 in / $0.30 out
- Meta-Llama-3.1-70B-Instruct$0.40 in / $0.40 out
Capability lists this model is in
Последнее обновление:
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.