Llama 3.2 90B Vision Instruct
meta/llama-3-2-90b-vision-instructمن Meta · العائلة: llama · أُصدِر 2024-09-25 · تاريخ المعرفة: 2023-12
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.
Coding42
- Tool calling40/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)0/20
- Provider availability2/10
Agents37
- Tool calling35/35
- Structured output0/25
- Reasoning0/15
- Output token limit0/15
- Provider availability2/10
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 context0
- Context ≥ 100K0/100
Vision65
- Accepts image input50/50
- Context window (10K → 1M)3/30
- Has published price10/10
- Provider availability2/10
Production-readiness61
- Number of independent providers10/40
- Has published per-token price20/20
- Context window ≥ 8K8/15
- No data inconsistencies across providers8/10
- 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. |
تفاصيل التسعير
السعر المُوصى به من io-net · meta-llama/Llama-3.2-90B-Vision-Instruct
أرخص مزود: nvidia · Unknown إدخال + Unknown إخراج
متاح لدى 2 مزود
| المزود | معرف نموذج المزود | إدخال / 1M | إخراج / 1M | السياق | تاريخ الإصدار |
|---|---|---|---|---|---|
| IO.NET io-net | meta-llama/Llama-3.2-90B-Vision-Instruct | $0.350 | $0.400 | 16K | 2024-09-25 |
| Nvidia nvidia | meta/llama-3.2-90b-vision-instruct | Unknown | Unknown | 128K | 2024-09-25 |
اختلافات في بيانات المزودين
- context_window varies: 128000, 16000
يبلِّغ المزودون قيمًا مختلفة لهذا النموذج. تستخدم الحقائق السريعة أعلاه مزودًا تمثيليًا؛ راجع الجدول للتفاصيل لكل مزود.
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 16K tokens, with a max output of 4K 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 Llama-3.3-70B-Instruct, Llama-3.1-8B-Instruct, Muse Spark 1.1. 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 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
More Meta models
- Llama-3.3-70B-Instruct$0.05 in / $0.23 out
- Llama-3.1-8B-Instruct$0.02 in / $0.03 out
- Muse Spark 1.1$1.25 in / $4.25 out
- Muse Spark 1.2$1.25 in / $4.25 out
- Muse Spark 1.3$1.25 in / $4.25 out
Capability lists this model is in
آخر تحديث:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.