Approved models
11
Records published from this collection
Provider information
lab
Review approach
Verify each model’s source, terms, capabilities, and current availability
fixie-ai is recorded as the provider or repository publisher for 5 model records in this editorial directory. The collection brings those records together for research, task discovery, and careful comparison.
Provider grouping is not a statement about current API availability, pricing, commercial support, or which model is best. Those details can vary by release and host, so each model page preserves source links and leaves unknown information unfilled rather than inferred.
Review the individual record for licenses, modalities, limits, deployment requirements, and evaluation evidence. Approval controls whether this collection and its models can be visible to search engines or included in the sitemap.
Review each record individually; collection membership does not imply a recommendation or guarantee of availability.
| Model | Capability▼ | Context | Input $/1M | Output $/1M | Speed |
|---|---|---|---|---|---|
| fixie-ai/ultravox-v0_2 fixie-ai | 5.0 | — | — | — | — |
| fixie-ai/ultravox-v0_3 fixie-ai | 5.0 | — | — | — | — |
| fixie-ai/ultravox-v0_4 fixie-ai | 5.0 | — | — | — | — |
| fixie-ai/ultravox-v0_5-llama-3_1-8b fixie-ai | 5.0 | — | — | — | — |
| fixie-ai/ultravox-v0_5-llama-3_2-1b fixie-ai | 5.0 | — | — | — | — |
| fixie-ai/ultravox-v0_5-llama-3_3-70b fixie-ai | 5.0 | — | — | — | — |
| fixie-ai/ultravox-v0_6-gemma-3-27b fixie-ai | 5.0 | — | — | — | — |
| fixie-ai/ultravox-v0_6-llama-3_1-8b fixie-ai | 5.0 | — | — | — | — |
| fixie-ai/ultravox-v0_6-llama-3_3-70b fixie-ai | 5.0 | — | — | — | — |
| fixie-ai/ultravox-v0_6-qwen-3-32b fixie-ai | 5.0 | — | — | — | — |
| fixie-ai/ultravox-v0_7-glm-4_6 fixie-ai | 5.0 | — | — | — | — |
11 models · click a column to sort
About the capability score: a 0–100 figure SyncDev calculates from each vendor's published specifications — context window, reasoning support, input modalities, tool calling, maximum output and how recently the model shipped. It measures breadth of capability, not benchmark performance, so a higher-scoring model is not automatically the better choice for your task.