Llama 3.1 8B Instruct is $0.02 cheaper per 1M input tokens (48.7% lower; 1.95x difference).
API cost decision in 10 seconds
🔥gpt-oss-120b vs Llama 3.1 8B Instruct
Pick Llama 3.1 8B Instruct when budget is the priority.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Llama 3.1 8B Instruct when budget is the priority.
On the standard 1M input plus 500K output workload, Llama 3.1 8B Instruct is estimated at $0.04 vs $0.13 for gpt-oss-120b, saving $0.08 (65.1% lower).
Cost-first pickLlama 3.1 8B Instruct
Context-first pickBoth models
Sample savings$0.0865.1%
10x traffic gap$0.84
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $0.84. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Llama 3.1 8B Instruct stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | gpt-oss-120b | Llama 3.1 8B Instruct |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Llama 3.1 8B Instruct | $0.29 | $0.12 |
| Balanced workload | 1M input + 1M output | Llama 3.1 8B Instruct | $0.22 | $0.07 |
| Output-heavy chatbot | 1M input + 5M output | Llama 3.1 8B Instruct | $0.94 | $0.27 |
Llama 3.1 8B Instruct is $0.13 cheaper per 1M output tokens (72.2% lower; 3.6x difference).
Both models report the same context window at 131.07K tokens.
Llama 3.1 8B Instruct is $0.08 cheaper on the standard workload (65.1% lower).
Estimate your workload cost
Your Workload Cost
This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.
Quick Decision
Llama 3.1 8B Instruct has the lower input price; Llama 3.1 8B Instruct has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Llama 3.1 8B Instruct is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.13 for gpt-oss-120b and $0.04 for Llama 3.1 8B Instruct.
Choose gpt-oss-120b when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
Choose Llama 3.1 8B Instruct when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, Llama 3.1 8B Instruct is estimated at $0.04 vs $0.13 for gpt-oss-120b, saving $0.08 (65.1% lower).
- Llama 3.1 8B Instruct is $0.08 cheaper on the standard workload (65.1% lower).
- Llama 3.1 8B Instruct is $0.02 cheaper per 1M input tokens (48.7% lower; 1.95x difference).
- Llama 3.1 8B Instruct is $0.13 cheaper per 1M output tokens (72.2% lower; 3.6x difference).
- Both models report the same context window at 131.07K tokens.
| Feature | 🔥gpt-oss-120b (OpenAI) | Llama 3.1 8B Instruct (Meta) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.039 | $0.02 |
| Completion Price per 1M tokens | $0.18 | $0.05 |
| Sample Workload Cost 1M input + 500K output | $0.13 | $0.04 |
| Context Window | 131.07K | 131.07K |
| Release Date | ||
| Popularity | #20 | #40 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Llama 3.1 8B Instruct | On the standard 1M input plus 500K output workload, Llama 3.1 8B Instruct is estimated at $0.04 vs $0.13 for gpt-oss-120b, saving $0.08 (65.1% lower). |
| High-volume input processing | Llama 3.1 8B Instruct | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Llama 3.1 8B Instruct | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Tie | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- gpt-oss-120b (free) can replace gpt-oss-120b when lower sample workload cost matters most: $0.
- gpt-oss-20b (free) can replace gpt-oss-120b when lower sample workload cost matters most: $0.
- gpt-oss-20b can replace gpt-oss-120b when lower sample workload cost matters most: $0.1.
- Llama 3.3 70B Instruct (free) can replace Llama 3.1 8B Instruct when lower sample workload cost matters most: $0.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash (free) offers 1.05M context with $0 sample workload cost.
- Lyria 3 Clip Preview offers 1.05M context with $0 sample workload cost.
- Lyria 3 Pro Preview offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash · DeepSeek · #1
- Hy3 preview · Tencent · #2
- Claude Opus 4.7 · Anthropic · #3
- Claude Sonnet 4.6 · Anthropic · #4
Cheaper alternatives
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Open Meta modelsgpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...