Llama 3.3 Groq Chat: pricing, context window and benchmarks
Llama 3.3 Groq Chat is a multimodal model from Groq. It offers a 32,768-token context window, costs $4.06 per million input tokens and $19.98 per million output tokens, and averages 76.8 across the index's benchmark suite.
Pricing
Llama 3.3 Groq Chat costs $4.06 per million input tokens and $19.98 per million output tokens. A blended 3:1 input-to-output mix works out to about $8.04 per million tokens. Cached input is listed at $0.48 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $4.06 | per 1M tokens |
| Output | $19.98 | per 1M tokens |
| Cached input | $0.48 | per 1M tokens |
| Blended 3:1 | $8.04 | estimate per 1M tokens |
| 1M in + 1M out | $24.04 | estimate |
Benchmarks
Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 79.6 | 192 | 68th | |
| GPQA Diamond | 73.3 | 193 | 68th | |
| SWE-bench Verified | 66.9 | 171 | 72th | |
| HumanEval | 80.2 | 226 | 62th | |
| MATH-500 | 78.2 | 252 | 58th | |
| AIME 2025 | 74.2 | 172 | 71th | |
| LiveCodeBench | 71.3 | 163 | 73th | |
| IFEval | 83.6 | 226 | 62th | |
| TruthfulQA | 77.4 | 270 | 55th | |
| HellaSwag | 87.2 | 167 | 72th | |
| MMMU | 72.9 | 223 | 63th | |
| Arena Elo | 1412.7 | 178 | 70th |
What Llama 3.3 Groq Chat is good for
Llama 3.3 Groq Chat is an open-weight model, so it can be self-hosted or run through a third-party inference provider. That matters for data residency, fine-tuning and long-run cost control. At $4.06 per million input tokens (hosted list price) and a 32,768-token context window, it is a practical option for teams that want more control than a closed API allows.
Strengths
- Open weights make self-hosting, fine-tuning and data-residency review possible.
- Accepts more than text, including image input where the provider supports it.
Trade-offs
- No standout weakness in the indexed specifications, but real-world behaviour still needs testing.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 3.1 Turbo | Together AI | 200000 | $4.17 | 76.8 |
| Llama 3.3 Groq | Groq | 32768 | $3.98 | 76.8 |
| Llama 3.3 Groq Chat | Groq | 32768 | $4.06 | 76.8 |
| Magistral Chat | Mistral AI | 128000 | $4.33 | 76.8 |
| ERNIE 4.0 | Baidu | 32768 | $11.37 | 76.7 |
| Llama 3.1 Turbo Instruct | Together AI | 32768 | $4.21 | 76.7 |
FAQ
How much does Llama 3.3 Groq Chat cost?
Llama 3.3 Groq Chat is listed at $4.06 per million input tokens and $19.98 per million output tokens. Cached input is $0.48 per million tokens. A blended 3:1 input-to-output mix is about $8.04 per million tokens.
What is the context window of Llama 3.3 Groq Chat?
Llama 3.3 Groq Chat has a context window of 32,768 tokens and can emit up to 4,096 output tokens per request in this index.
Is Llama 3.3 Groq Chat open weights?
Yes. Llama 3.3 Groq Chat is listed as an open-weight model under a open weights licence.
How does Llama 3.3 Groq Chat score on benchmarks?
Llama 3.3 Groq Chat averages 76.8 across the scored benchmarks in this index, ranking #198 of 600 models. Its strongest relative result is Arena Elo at 1412.7.
What is Llama 3.3 Groq Chat best for?
Llama 3.3 Groq Chat is an open-weight model, so it can be self-hosted or run through a third-party inference provider. That matters for data residency, fine-tuning and long-run cost control. At $4.06 per million input tokens (hosted list price) and a 32,768-token context window, it is a practical option for teams that want more control than a closed API allows.