As of August 20, 2026, Llama 3.1 8B Instruct is 80% cheaper per million tokens than Laguna S 2.1. Laguna S 2.1 is $0.10 / $0.20 per million input/output tokens versus Llama 3.1 8B Instruct at $0.03 / $0.03. Sources: https://poolside.ai and https://llama.meta.com/
Sources: Poolside pricing (https://poolside.ai); Meta pricing (https://llama.meta.com/)
Laguna S 2.1
Poolside
Input
$0.10
Output
$0.20
Llama 3.1 8B Instruct
Meta
Input
$0.03
Output
$0.03
Token pricing, specs, and benchmarks side by side
Laguna S 2.1Llama 3.1 8B InstructVerdict
Both models are closely matched on benchmarks. Llama 3.1 8B Instruct has the pricing advantage, making it the better value unless Laguna S 2.1's specific capabilities are critical to your workflow.
As of August 20, 2026, Llama 3.1 8B Instruct is 80% cheaper on blended LLM API pricing. Llama 3.1 8B Instruct costs $0.03 per million input tokens and $0.03 per million output tokens ($0.06 blended 1M-in + 1M-out). Laguna S 2.1 costs $0.10 / $0.20 per million tokens ($0.30 blended). Sources: https://poolside.ai and https://llama.meta.com/. The cheapest LLM for your app still depends on how many output tokens you generate.
Laguna S 2.1 Poolside API pricing is $0.10 input and $0.20 output per million tokens via Poolside. Llama 3.1 8B Instruct Meta API pricing is $0.03 input and $0.03 output per million tokens via Meta. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Laguna S 2.1 has a published SWE-bench Pro score of 59.4%. Llama 3.1 8B Instruct does not have that eval on this page yet.
Laguna S 2.1 supports a 1M token context window, while Llama 3.1 8B Instruct supports 131K tokens. Laguna S 2.1 offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Shared benchmark scores for Laguna S 2.1 and Llama 3.1 8B Instruct are still limited. Check the comparison table for the evals each model has published. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Both Laguna S 2.1 and Llama 3.1 8B Instruct are production API models. For cost-sensitive production traffic, Llama 3.1 8B Instruct has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Yes. Call Laguna S 2.1 through Poolside and Llama 3.1 8B Instruct through Meta with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
List rates are the latest published Poolside API pricing and Meta API pricing, quoted per million tokens. Official rate sheets: https://poolside.ai and https://llama.meta.com/. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
Laguna S 2.1 supports up to an unspecified number of output tokens per request, while Llama 3.1 8B Instruct supports up to 131K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Llama 3.1 8B Instruct has a measured throughput of approximately 42 tokens/second. Throughput data for Laguna S 2.1 is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Laguna S 2.1 or Llama 3.1 8B Instruct from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
This comparison covers API pricing, context window, throughput, and benchmark scores. Laguna S 2.1 costs $0.10/M input and $0.20/M output. Llama 3.1 8B Instruct costs $0.03/M input and $0.03/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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