Llama 3.1 8B Instruct model profile
Evidence snapshot:
Llama 3.1 8B Instruct is a Meta model profile with a 131,072-token context window. The dated catalog snapshot records text modalities and interfaces for prompt caching, structured output, text generation, tool calling.
Llama 3.1 8B Instruct is an independent knowledge profile. It does not claim that Kendr hosts the model, quote a Kendr customer price, promise API availability, or advertise a Kendr routing receipt.
Llama 3.1 8B Instruct accepts text and returns text. The snapshot records prompt caching, structured output, text generation, and tool calling as capabilities or interfaces.
The dated reference snapshot lists $0.05 input and $0.08 output per million tokens. Cached input is $0.025 per million tokens.
The 2026-08-12 snapshot includes 1 Artificial Analysis index. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.
Llama 3.1 8B Instruct ranked #80 in the cited trailing-7-day third-party catalog usage dataset as of 2026-08-12. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.
Profile data was reviewed for the 2026-08-12 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.
Profile facts
- Profile type
- Model research profile
- Provider or publisher
- Meta
- Context window
- 131,072 tokens
- Snapshot date
- 2026-08-12
- Reference catalog ID
- meta-llama/llama-3.1-8b-instruct
Context, modalities, and identity
Llama 3.1 8B Instruct accepts text and returns text. The snapshot records prompt caching, structured output, text generation, and tool calling as capabilities or interfaces.
- Provider or publisher
- Meta
- Context window
- 131,072 tokens
- Maximum output
- 131,072 tokens
- Input modalities
- text
- Output modalities
- text
- Knowledge cutoff
- 2023-12-31
Capabilities and supported controls
Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.
- Supported parameters
- frequency_penalty, logit_bias, logprobs, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p
- prompt caching
- structured output
- text generation
- tool calling
Dated pricing snapshot
The dated reference snapshot lists $0.05 input and $0.08 output per million tokens. Cached input is $0.025 per million tokens.
These are dated third-party reference prices, not Kendr prices or an availability offer. Routes, tiers, caching, region, and provider policy can change the landed price.
- Price date
- 2026-08-12
- Input
- $0.05 per 1M tokens
- Cached input
- $0.025 per 1M tokens
- Output
- $0.08 per 1M tokens
Benchmark evidence and limitations
The 2026-08-12 snapshot includes 1 Artificial Analysis index. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.
Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.
- Coding Index
- 5.4
Popularity and market context
Llama 3.1 8B Instruct ranked #80 in the cited trailing-7-day third-party catalog usage dataset as of 2026-08-12. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.
- Third-party catalog rank
- #80
- Global market share
- Not inferred
- Observation date
- 2026-08-12
Frequently asked questions
What is Llama 3.1 8B Instruct?
Llama 3.1 8B Instruct is a Meta model profile with a 131,072-token context window. The dated catalog snapshot records text modalities and interfaces for prompt caching, structured output, text generation, tool calling.
What context window does Llama 3.1 8B Instruct have?
The dated profile lists 131,072 tokens of context and up to 131,072 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.
What benchmark evidence is available for Llama 3.1 8B Instruct?
The 2026-08-12 snapshot includes 1 Artificial Analysis index. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable. Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.
Is Llama 3.1 8B Instruct available through Kendr?
This is an independent knowledge profile, not a Kendr-hosted availability claim. Check Kendr's live public model API for currently enabled Kendr aliases.
Does the popularity rank represent Llama 3.1 8B Instruct's global market share?
Llama 3.1 8B Instruct ranked #80 in the cited trailing-7-day third-party catalog usage dataset as of 2026-08-12. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share. No global market-share percentage is inferred when the source does not publish one.
Sources and evidence dates
- Llama 3.1 8B Instruct third-party catalog record (catalog, checked 2026-08-12)
- Third-party model catalog methodology (methodology, checked 2026-08-12)
- Meta official model documentation (primary, checked 2026-08-12)
- Artificial Analysis capability indices methodology (benchmark, checked 2026-08-12)