tiennm99/cheahjs-free-llm-api-resources
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samba: move from free to trial credits

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Jun Siang Cheah committed 2025-01-30 20:57:51 +08:00
1 parent 0e1087e320
commit cf1d8934c3
2 files changed
+28 -27
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README.md
+14 -14
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@@ -93,19 +93,7 @@ This lists various services that provide free access or credits towards API-base
<td>Limited to models smaller than 10GB.<br>Some popular models are supported even if they exceed 10GB.</td>
<td>Various open models</td>
<td><a href="https://huggingface.co/docs/api-inference/rate-limits" target="_blank">1,000 requests/day (with an account)</a></td>
</tr><tr><td rowspan="12"><a href="https://cloud.sambanova.ai/" target="_blank">SambaNova Cloud</a></td><td rowspan="12"></td><td>Llama 3.1 8B</td><td>30 requests/minute</td></tr>
<tr><td>Llama 3.1 70B</td><td>20 requests/minute</td></tr>
<tr><td>Llama 3.1 405B</td><td>10 requests/minute</td></tr>
<tr><td>Llama 3.2 1B</td><td>30 requests/minute</td></tr>
<tr><td>Llama 3.2 3B</td><td>30 requests/minute</td></tr>
<tr><td>Llama 3.2 11B</td><td>10 requests/minute</td></tr>
<tr><td>Llama 3.2 90B</td><td>1 requests/minute</td></tr>
<tr><td>Llama 3.3 70B</td><td>20 requests/minute</td></tr>
<tr><td>Llama Guard 3 8B</td><td>30 requests/minute</td></tr>
<tr><td>Qwen 2.5 72B</td><td>20 requests/minute</td></tr>
<tr><td>Qwen 2.5 Coder 32B</td><td>20 requests/minute</td></tr>
<tr><td>QwQ 32B Preview</td><td>10 requests/minute</td></tr>
<tr>
</tr><tr>
<td rowspan="2"><a href="https://cloud.cerebras.ai/" target="_blank">Cerebras</a></td>
<td rowspan="2">Free tier restricted to 8K context</td>
<td>Llama 3.1 8B</td>
@@ -274,7 +262,19 @@ This lists various services that provide free access or credits towards API-base
</tr>
<tr>
<td><a href="https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/gemini-experimental" target="_blank">Gemini Pro Experimental</a></td>
</tr></tbody></table>
</tr></tbody></table><tr><td rowspan="12"><a href="https://cloud.sambanova.ai/" target="_blank">SambaNova Cloud</a></td><td rowspan="12">$5 for 3 months</td><td>Llama 3.1 8B</td><td>30 requests/minute</td></tr>
<tr><td>Llama 3.1 70B</td><td>20 requests/minute</td></tr>
<tr><td>Llama 3.1 405B</td><td>10 requests/minute</td></tr>
<tr><td>Llama 3.2 1B</td><td>30 requests/minute</td></tr>
<tr><td>Llama 3.2 3B</td><td>30 requests/minute</td></tr>
<tr><td>Llama 3.2 11B</td><td>10 requests/minute</td></tr>
<tr><td>Llama 3.2 90B</td><td>1 requests/minute</td></tr>
<tr><td>Llama 3.3 70B</td><td>20 requests/minute</td></tr>
<tr><td>Llama Guard 3 8B</td><td>30 requests/minute</td></tr>
<tr><td>Qwen 2.5 72B</td><td>20 requests/minute</td></tr>
<tr><td>Qwen 2.5 Coder 32B</td><td>20 requests/minute</td></tr>
<tr><td>QwQ 32B Preview</td><td>10 requests/minute</td></tr>
## Providers with trial credits
src/pull_available_models.py
+14 -13
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@@ -861,19 +861,6 @@ def main():
<td><a href="https://huggingface.co/docs/api-inference/rate-limits" target="_blank">1,000 requests/day (with an account)</a></td>
</tr>"""
for idx, model in enumerate(samba_models):
table += "<tr>"
if idx == 0:
table += f'<td rowspan="{len(samba_models)}">'
table += '<a href="https://cloud.sambanova.ai/" target="_blank">SambaNova Cloud</a>'
table += "</td>"
table += f'<td rowspan="{len(samba_models)}"></td>'
table += f"<td>{model['name']}</td>"
table += f"<td>{get_human_limits(model)}</td>"
table += "</tr>\n"
table += """<tr>
<td rowspan="2"><a href="https://cloud.cerebras.ai/" target="_blank">Cerebras</a></td>
<td rowspan="2">Free tier restricted to 8K context</td>
@@ -1010,6 +997,20 @@ def main():
trial_table += f'<td rowspan="{len(hyperbolic_models)}"></td>'
trial_table += f"<td>{model['name']}</td>"
trial_table += "</tr>\n"
for idx, model in enumerate(samba_models):
table += "<tr>"
if idx == 0:
table += f'<td rowspan="{len(samba_models)}">'
table += '<a href="https://cloud.sambanova.ai/" target="_blank">SambaNova Cloud</a>'
table += "</td>"
table += f'<td rowspan="{len(samba_models)}">$5 for 3 months</td>'
table += f"<td>{model['name']}</td>"
table += f"<td>{get_human_limits(model)}</td>"
table += "</tr>\n"
if MISSING_MODELS:
logger.warning("Missing models:")
logger.warning(list(MISSING_MODELS))