Last refreshed 2026-07-09. Next refresh: weekly.
Why use Llama 3.2 90B Vision Instruct on Fireworks AI?
Fireworks AI offers Llama 3.2 90B Vision Instruct with pay-as-you-go pricing at $0.90/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Compare Llama 3.2 90B Vision Instruct across 6 providers to find the best fit for your use caseInput / 1M
$0.90
Output / 1M
$0.90
Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install openaiAuth
export FIREWORKS_API_KEY=...Call
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],Model ID
accounts/fireworks/models/llama-v3p2-90b-vision-instructRequest example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/llama-v3p2-90b-vision-instruct",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/llama-v3p2-90b-vision-instruct", not the LLMReference slug "llama-3.2-90b-vision-instruct".
- Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
- The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.
Compare Llama 3.2 90B Vision Instruct Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Fireworks AI | $0.90 | $0.90 |
| NVIDIA NIM | — | — |
| Bitdeer AI | $0.15 | $0.45 |
| AWS Bedrock | $1.35 | $1.80 |
| Microsoft Foundry | $2.04 | $2.04 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.90 |
| Output tokens | $0.90 |
Capabilities
VisionMultimodal
About Llama 3.2 90B Vision Instruct
Instruction-tuned 90B Llama 3.2 Vision model for higher-capability image reasoning, visual question answering, visual grounding, and captioning. NVIDIA NIM lists text plus image input, text output, and a 128K context window for the Llama 3.2 Vision collection.
Get Started
Model Specs
Released2024-09-25
Parameters88.8B
Context128k
ArchitectureDecoder Only
Knowledge cutoff2024-03