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feat(genapi): add parallel tool calling support (#5323)
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pages/managed-inference/reference-content/model-catalog.mdx

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@@ -91,6 +91,7 @@ google/gemma-3-27b-it:bf16
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```
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| Attribute | Value |
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|-----------|-------|
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| Supports parallel tool calling | No |
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| Supported image formats | PNG, JPEG, WEBP, and non-animated GIFs |
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| Maximum image resolution (pixels) | 896x896 |
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| Token dimension (pixels)| 56x56 |
@@ -103,6 +104,7 @@ This model was optimized to have a dense knowledge and faster tokens throughput
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| Attribute | Value |
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|-----------|-------|
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| Supports parallel tool calling | Yes |
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| Supported images formats | PNG, JPEG, WEBP, and non-animated GIFs |
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| Maximum image resolution (pixels) | 1540x1540 |
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| Token dimension (pixels)| 28x28 |
@@ -123,6 +125,7 @@ It can analyze images and offer insights from visual content alongside text.
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| Attribute | Value |
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|-----------|-------|
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| Supports parallel tool calling | Yes |
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| Supported images formats | PNG, JPEG, WEBP, and non-animated GIFs |
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| Maximum image resolution (pixels) | 1024x1024 |
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| Token dimension (pixels)| 16x16 |
@@ -148,6 +151,10 @@ allenai/molmo-72b-0924:fp8
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Released December 6, 2024, Meta’s Llama 3.3 70b is a fine-tune of the [Llama 3.1 70b](/managed-inference/reference-content/model-catalog/#llama-31-70b-instruct) model.
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This model is still text-only (text in/text out). However, Llama 3.3 was designed to approach the performance of Llama 3.1 405B on some applications.
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| Attribute | Value |
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|-----------|-------|
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| Supports parallel tool calling | Yes |
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#### Model name
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```
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meta/llama-3.3-70b-instruct:fp8
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Released July 23, 2024, Meta’s Llama 3.1 is an iteration of the open-access Llama family.
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Llama 3.1 was designed to match the best proprietary models and outperform many of the available open source on common industry benchmarks.
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| Attribute | Value |
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|-----------|-------|
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| Supports parallel tool calling | Yes |
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#### Model names
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```
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meta/llama-3.1-70b-instruct:fp8
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Released July 23, 2024, Meta’s Llama 3.1 is an iteration of the open-access Llama family.
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Llama 3.1 was designed to match the best proprietary models and outperform many of the available open source on common industry benchmarks.
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| Attribute | Value |
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|-----------|-------|
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| Supports parallel tool calling | Yes |
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#### Model names
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```
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meta/llama-3.1-8b-instruct:fp8
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Released January 21, 2025, Deepseek’s R1 Distilled Llama 70B is a distilled version of the Llama model family based on Deepseek R1.
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DeepSeek R1 Distill Llama 70B is designed to improve the performance of Llama models on reasoning use cases such as mathematics and coding tasks.
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| Attribute | Value |
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|-----------|-------|
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| Supports parallel tool calling | No |
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#### Model name
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```
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deepseek/deepseek-r1-distill-llama-70b:fp8
@@ -247,6 +266,10 @@ Mistral Nemo is a state-of-the-art transformer model of 12B parameters, built by
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This model is open-weight and distributed under the Apache 2.0 license.
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It was trained on a large proportion of multilingual and code data.
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| Attribute | Value |
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|-----------|-------|
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| Supports parallel tool calling | Yes |
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#### Model name
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```
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mistral/mistral-nemo-instruct-2407:fp8
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Qwen2.5-coder is your intelligent programming assistant familiar with more than 40 programming languages.
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With Qwen2.5-coder deployed at Scaleway, your company can benefit from code generation, AI-assisted code repair, and code reasoning.
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| Attribute | Value |
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|-----------|-------|
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| Supports parallel tool calling | No |
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#### Model name
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```
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qwen/qwen2.5-coder-32b-instruct:int8

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