StableLM 2 Chat on LiveCodeBench: score, rank and what it means
StableLM 2 Chat scores 55.7 on LiveCodeBench, placing it #399 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.
Score distribution
The chart shows the top 10 models on LiveCodeBench, with StableLM 2 Chat highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 2 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 3 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 4 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 5 | Grok 4 Turbo | xAI | 1000000 | $19.21 | 86.7 |
| 6 | GPT-5.1 Turbo | OpenAI | 2000000 | $19.19 | 86.1 |
| 7 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 8 | GPT-5.2 Reasoning | OpenAI | 1000000 | $20.98 | 87.5 |
| 9 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 10 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
What this score means
On LiveCodeBench, StableLM 2 Chat sits at #399 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 29.4 points. The median model in this index scores 64.7, which puts StableLM 2 Chat below the midpoint.
Stability AI models average 42.9 on this benchmark. StableLM 2 Chat is 12.8 points above that provider line, so it is a stronger result than the average Stability AI model.
Among open-weight models, the average is 59.1. StableLM 2 Chat is 3.4 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 55.7 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 $1.79 per million input tokens, StableLM 2 Chat is below the median input price of $4.00 across the 600 models scored on LiveCodeBench. 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 |
|---|---|---|---|---|
| Nemotron Nano Instruct | NVIDIA | 32768 | $2.33 | 67.4 |
| Embed 4 Reasoning | Cohere | 4096 | $5.50 | 65.3 |
| SmolLM3 Instruct | Hugging Face | 8192 | $1.69 | 63.6 |
| StableLM 2 Instruct | Stability AI | 16384 | $1.93 | 65.2 |
| StableLM 2 Chat | Stability AI | 8192 | $1.79 | 64.6 |
| ERNIE 4.5 Nano | Baidu | 32768 | $6.01 | 65.6 |
| Phi-3.5 Base | Microsoft | 65536 | $2.24 | 66.6 |
Other benchmarks for StableLM 2 Chat
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 66.4 | 436 | 27th | |
| GPQA Diamond | 61.8 | 392 | 35th | |
| SWE-bench Verified | 51.6 | 410 | 32th | |
| HumanEval | 69.7 | 400 | 33th | |
| MATH-500 | 68.0 | 401 | 33th | |
| AIME 2025 | 52.6 | 439 | 27th | |
| IFEval | 74.9 | 400 | 33th | |
| TruthfulQA | 70.1 | 399 | 34th | |
| HellaSwag | 78.7 | 396 | 34th | |
| MMMU | 61.0 | 421 | 30th | |
| Arena Elo | 1297.5 | 425 | 29th |
FAQ
What score does StableLM 2 Chat get on LiveCodeBench?
StableLM 2 Chat scores 55.7 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.
How does StableLM 2 Chat rank on LiveCodeBench?
It ranks #399 of 600 models, in the 34th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.
Is StableLM 2 Chat good at LiveCodeBench?
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 LiveCodeBench score calculated?
LiveCodeBench 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 StableLM 2 Chat cost?
StableLM 2 Chat costs $1.79 per million input tokens and $9.72 per million output tokens.