| Signal | Olmo 3.1 32B Think | Delta | Llama 3.1 8B Instruct |
|---|---|---|---|
Capabilities | 50 | -- | |
Benchmarks | 52 | +0 | |
Pricing | 100 | 0 | |
Context window size | 76 | +10 | |
Recency | 100 | +80 | |
Output Capacity | 80 | +10 | |
| Overall Result | 4 wins | of 6 | 1 wins |
Score History
52.6
current score
Olmo 3.1 32B Think
right now
52.1
current score
Allen AI
Meta
Llama 3.1 8B Instruct saves you $35.50/month
That's $426.00/year compared to Olmo 3.1 32B Think at your current usage level of 100K calls/month.
| Metric | Olmo 3.1 32B Think | Llama 3.1 8B Instruct | Winner |
|---|---|---|---|
| Overall Score | 53 | 52 | Olmo 3.1 32B Think |
| Rank | #109 | #110 | Olmo 3.1 32B Think |
| Quality Rank | #109 | #110 | Olmo 3.1 32B Think |
| Adoption Rank | #109 | #110 | Olmo 3.1 32B Think |
| Parameters | 32B | 8B | -- |
| Context Window | 66K | 16K | Olmo 3.1 32B Think |
| Pricing | $0.15/$0.50/M | $0.02/$0.05/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Olmo 3.1 32B Think |
| Benchmarks | 52 | 51 | Olmo 3.1 32B Think |
| Pricing | 100 | 100 | Llama 3.1 8B Instruct |
| Context window size | 76 | 67 | Olmo 3.1 32B Think |
| Recency | 100 | 20 | Olmo 3.1 32B Think |
| Output Capacity | 80 | 70 | Olmo 3.1 32B Think |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 53/100 (rank #109), placing it in the top 63% of all 290 models tracked.
Scores 52/100 (rank #110), placing it in the top 62% of all 290 models tracked.
With only a 1-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Llama 3.1 8B Instruct offers 89% better value per quality point. At 1M tokens/day, you'd spend $1.05/month with Llama 3.1 8B Instruct vs $9.75/month with Olmo 3.1 32B Think - a $8.70 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Llama 3.1 8B Instruct also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (66K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.05/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (53/100) correlates with better nuance, coherence, and style in long-form content
Olmo 3.1 32B Think and Llama 3.1 8B Instruct are extremely close in overall performance (only 0.5 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Olmo 3.1 32B Think
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.1 8B Instruct
89% lower pricing; better value at scale
Best for Reliability
Olmo 3.1 32B Think
Higher uptime and faster response speeds
Best for Prototyping
Olmo 3.1 32B Think
Stronger community support and better developer experience
Best for Production
Olmo 3.1 32B Think
Wider enterprise adoption and proven at scale
by Allen AI
| Capability | Olmo 3.1 32B Think | Llama 3.1 8B Instruct |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Allen AI
Meta
Llama 3.1 8B Instruct saves you $0.7740/month
That's 89% cheaper than Olmo 3.1 32B Think at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Olmo 3.1 32B Think | Llama 3.1 8B Instruct |
|---|---|---|
| Context Window | 66K | 16K |
| Max Output Tokens | 65,536 | 16,384 |
| Open Source | Yes | Yes |
| Created | Dec 16, 2025 | Jul 23, 2024 |
Olmo 3.1 32B Think scores 53/100 (rank #109) compared to Llama 3.1 8B Instruct's 52/100 (rank #110), giving it a 1-point advantage. Olmo 3.1 32B Think is the stronger overall choice, though Llama 3.1 8B Instruct may excel in specific areas like cost efficiency.
Olmo 3.1 32B Think is ranked #109 and Llama 3.1 8B Instruct is ranked #110 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Llama 3.1 8B Instruct is cheaper at $0.05/M output tokens vs Olmo 3.1 32B Think's $0.50/M output tokens - 10.0x more expensive. Input token pricing: Olmo 3.1 32B Think at $0.15/M vs Llama 3.1 8B Instruct at $0.02/M.
Olmo 3.1 32B Think has a larger context window of 65,536 tokens compared to Llama 3.1 8B Instruct's 16,384 tokens. A larger context window means the model can process longer documents and conversations.