Llama 3.1 70B Instruct model profile
Evidence snapshot:
Llama 3.1 70B Instruct is a Meta model profile with a 131,072-token context window. The dated catalog snapshot records text modalities and interfaces for structured output, text generation, tool calling.
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...
Llama 3.1 70B Instruct is a reference profile: Meta publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.
Llama 3.1 70B 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 70B Instruct accepts text and returns text. The snapshot records structured output, text generation, and tool calling as capabilities or interfaces.
The dated reference snapshot lists $0.4 input and $0.4 output per million tokens.
No comparable third-party benchmark value is present in the 2026-09-06 snapshot. Missing values are not estimated.
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated.
Profile data was reviewed for the 2026-09-06 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
- 2026-09-06
- Knowledge cutoff
- 2023-12-31
- Reference catalog ID
- meta-llama/llama-3.1-70b-instruct
When to pick Llama 3.1 70B Instruct
Llama 3.1 70B Instruct is a reference profile: Meta publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.
Each condition below is derived from this model's own values in the 2026-09-06 snapshot, compared only against models publishing the same field.
- Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
- Look elsewhere when you need to call it through Kendr today. This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.
- Look elsewhere when the prompt is long. The 131K-token context window is in the bottom quarter of the 163 models publishing a limit. Long documents need chunking or a wider-context route.
Context, modalities, and identity
Llama 3.1 70B Instruct accepts text and returns text. The snapshot records structured output, text generation, and tool calling as capabilities or interfaces.
- Provider or publisher
- Meta
- Context window
- 131,072 tokens
- Maximum output
- 16,384 tokens
- Input modalities
- text
- Output modalities
- text
- Knowledge cutoff
- 2023-12-31
Model overview
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...
- Reference model ID
- meta-llama/llama-3.1-70b-instruct
- Canonical version
- meta-llama/llama-3.1-70b-instruct
- Hugging Face ID
- meta-llama/Meta-Llama-3.1-70B-Instruct
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, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p
- structured output
- text generation
- tool calling
Dated pricing snapshot
The dated reference snapshot lists $0.4 input and $0.4 output 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
- 2026-09-06
- Input
- $0.4 per 1M tokens
- Cached input
- No verified rate
- Output
- $0.4 per 1M tokens
Provider routes, performance, and uptime
The snapshot retains 2 provider endpoints. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.
- Active provider endpoints
- 1
- Best p50 latency
- No recent metric
- Best p50 throughput
- No recent metric
- Availability with routing
- No recent metric
- Availability without routing
- No recent metric
- Performance date
- 2026-09-06
| Provider | Quantization | Input / 1M | Output / 1M | Cache read / 1M | Context | p50 latency | p50 throughput | Uptime (1d) |
|---|---|---|---|---|---|---|---|---|
| DeepInfra | fp8 | $0.4 / 1M | $0.4 / 1M | No verified rate | 131,072 tokens | No recent p50 | No recent p50 | 97.70% |
| Amazon Bedrock | unknown | $0.72 / 1M | $0.72 / 1M | No verified rate | 131,072 tokens | No recent p50 | No recent p50 | 99.15% |
Benchmark evidence and limitations
No comparable third-party benchmark value is present in the 2026-09-06 snapshot. Missing values are not estimated.
Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.
Popularity and market context
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated.
- Third-party catalog rank
- No verified rank
- Global market share
- Not inferred
- Observation date
- 2026-09-06
Frequently asked questions
When should I use Llama 3.1 70B Instruct?
Llama 3.1 70B Instruct is a reference profile: Meta publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call. Reach for it when the model has to call tools: Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose. Look elsewhere when you need to call it through Kendr today: This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr. Look elsewhere when the prompt is long: The 131K-token context window is in the bottom quarter of the 163 models publishing a limit. Long documents need chunking or a wider-context route.
What is Llama 3.1 70B Instruct?
Llama 3.1 70B Instruct is a Meta model profile with a 131,072-token context window. The dated catalog snapshot records text modalities and interfaces for structured output, text generation, tool calling.
What context window does Llama 3.1 70B Instruct have?
The dated profile lists 131,072 tokens of context and up to 16,384 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.
What benchmark evidence is available for Llama 3.1 70B Instruct?
No comparable third-party benchmark value is present in the 2026-09-06 snapshot. Missing values are not estimated. Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.
Is Llama 3.1 70B 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 70B Instruct's global market share?
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated. No global market-share percentage is inferred when the source does not publish one.
Sources and evidence dates
- Llama 3.1 70B Instruct third-party catalog record (catalog, checked 2026-09-06)
- Third-party model catalog methodology (methodology, checked 2026-09-06)
- Meta official model documentation (primary, checked 2026-09-06)