Multi Modal Vision Inputs
Together AI · Together AI
AI Inference Platform — Together AI
Evaluates Together AI's Multi-Modal Vision Inputs across 7 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Inference Platform eval coverage.
About Together AI
Together AI is an enterprise AI inference cloud providing fast, scalable access to leading open-source models via an OpenAI-compatible API. Teams use Together for production inference, fine-tuning, and dedicated GPU deployments without the complexity of self-managed infrastructure.
Sample tests· showing 3 of 7
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | Mixed content and SSRF risk; use https or base64 data URL per patterns. | ["Rejects or upgrades to https", "Uses signed HTTPS URL", "Does not fetch internal IP without policy"] | Pass / FailAi Platformhigh |
| 02 | Resize/compress before upload; document limits [REQUIRES-VERIFICATION numeric]. | ["Downscales image client-side", "Retries with JPEG", "Surfaces 400 clearly"] | Pass / FailAi Platformmedium |
| 03 | Use multimodal content array with type text and image_url on vision model. | {"criteria": ["Uses array content", "Correct vision model slug", "Preserves text question"], "pass_threshold": 3} | Pass / FailAi Platformhigh |
How this eval is graded
Grade the agent's response against expected.ideal_behavior and expected.rubric. Score 1-5 (4+ passes). Penalize failure_modes. For negative controls, correct behavior is refuse/abstain.
Rubric criteria
- Together Ai
- Ai Platform
- Multi Modal Vision Inputs
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ViewFrequently asked questions
What does the Multi Modal Vision Inputs eval for Together AI Together AI test?+
Evaluates Together AI's Multi-Modal Vision Inputs across 7 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Inference Platform eval coverage.
How is the Multi Modal Vision Inputs eval scored?+
The judge rubric: Grade the agent's response against expected.ideal_behavior and expected.rubric. Score 1-5 (4+ passes). Penalize failure_modes. For negative controls, correct behavior is refuse/abstain.
How many test cases does this eval pack include?+
The Multi Modal Vision Inputs pack for Together AI Together AI contains 7 test cases. 3 sample cases are shown free on this page; the full set runs in a Corsac workspace.
How do I run this eval?+
Sign up for Corsac, connect your model or agent endpoint, and run the Multi Modal Vision Inputs pack as-is or after customizing thresholds. Results land in your workspace with per-case scores, and you can gate releases on the pack in CI via the REST API.
Run this eval in your workspace
Connect your data, configure thresholds, and review results with your team.