Llama 3 DeepInfra Chat on HumanEval: score, rank and what it means
Llama 3 DeepInfra Chat scores 77.3 on HumanEval, placing it #304 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.
Score distribution
The chart shows the top 10 models on HumanEval, with Llama 3 DeepInfra Chat highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 2 | Gemini 3 Pro Pro | Google DeepMind | 200000 | $19.80 | 87.3 |
| 3 | o4 Max | OpenAI | 2000000 | $19.51 | 86.2 |
| 4 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 5 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 6 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 7 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 8 | Grok 4 Max | xAI | 2000000 | $19.70 | 86.6 |
| 9 | GPT-5.2 Turbo | OpenAI | 1000000 | $20.73 | 87.4 |
| 10 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
What this score means
On HumanEval, Llama 3 DeepInfra Chat sits at #304 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 19.5 points. The median model in this index scores 77.4, which puts Llama 3 DeepInfra Chat below the midpoint.
DeepInfra models average 68.8 on this benchmark. Llama 3 DeepInfra Chat is 8.5 points above that provider line, so it is a stronger result than the average DeepInfra model.
Among multimodal models, the average is 82.2. Llama 3 DeepInfra Chat is 4.9 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 77.3 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.
Price context
At $3.74 per million input tokens, Llama 3 DeepInfra Chat is below the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 3 Novita | Novita AI | 128000 | $3.70 | 74.4 |
| Sonar Pro Mini | Perplexity | 8192 | $8.02 | 70.3 |
| Auto Reasoning | OpenRouter | 65536 | $8.39 | 71.5 |
| Grok 3 Mini | xAI | 200000 | $9.67 | 73.9 |
| Llama 3 DeepInfra Chat | DeepInfra | 200000 | $3.74 | 75.0 |
| OLMo 2 | Allen Institute for AI | 65536 | $2.99 | 71.0 |
| Firefunction Reasoning | Fireworks AI | 8192 | $9.08 | 72.5 |
Other benchmarks for Llama 3 DeepInfra Chat
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 76.8 | 281 | 53th | |
| GPQA Diamond | 69.0 | 295 | 51th | |
| SWE-bench Verified | 65.5 | 204 | 66th | |
| MATH-500 | 80.6 | 198 | 67th | |
| AIME 2025 | 72.5 | 209 | 65th | |
| LiveCodeBench | 67.8 | 230 | 62th | |
| IFEval | 81.4 | 291 | 52th | |
| TruthfulQA | 78.3 | 244 | 59th | |
| HellaSwag | 83.6 | 299 | 50th | |
| MMMU | 72.1 | 240 | 60th | |
| Arena Elo | 1376.4 | 286 | 52th |
FAQ
What score does Llama 3 DeepInfra Chat get on HumanEval?
Llama 3 DeepInfra Chat scores 77.3 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.
How does Llama 3 DeepInfra Chat rank on HumanEval?
It ranks #304 of 600 models, in the 49th percentile. The leader is GPT-5.2 Pro at 96.8.
Is Llama 3 DeepInfra Chat good at HumanEval?
It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.
How is the HumanEval score calculated?
HumanEval is a coding benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.
What does Llama 3 DeepInfra Chat cost?
Llama 3 DeepInfra Chat costs $3.74 per million input tokens and $15.32 per million output tokens.