EVA-LLaMA-3.33-70B-v0.1
meta/eva-llama-3-33-70b-v0-1By Meta · family: llama · released 2025-09-25
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capabilities
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding1
- Tool calling0/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)0/20
- Provider availability1/10
Agents11
- Tool calling0/35
- Structured output0/25
- Reasoning0/15
- Output token limit10/15
- Provider availability1/10
JSON / structured output12
- Structured output / JSON mode0/50
- Tool calling0/20
- Temperature control0/10
- Price-friendly for high-volume12/20
Cost efficiency47
- Headline price (log-scaled)47/95
- Has prompt-cache pricing0/5
Long context0
- Context ≥ 100K0/100
Production-readiness58
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K8/15
- No data inconsistencies across providers10/10
- Official model (not derivative)15/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $11.03 $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $22.07 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $5.01 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $18.05 $0.02 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $25.28 $0.03 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Pricing detail
Recommended pricing from nano-gpt · EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
Available on 1 providers
| Provider | Provider model id | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|---|
| NanoGPT nano-gpt | EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1 | $2.01 | $2.01 | 16K | 2025-09-25 |
Frequently asked questions
How much does EVA-LLaMA-3.33-70B-v0.1 cost?
EVA-LLaMA-3.33-70B-v0.1 costs $2.01 per 1M input tokens and $2.01 per 1M output tokens, sourced from nano-gpt. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of EVA-LLaMA-3.33-70B-v0.1?
EVA-LLaMA-3.33-70B-v0.1 has a context window of 16K tokens, with a max output of 16K tokens per reply. This is the total combined size of prompt + completion.
Does EVA-LLaMA-3.33-70B-v0.1 support tool calling?
No. EVA-LLaMA-3.33-70B-v0.1 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does EVA-LLaMA-3.33-70B-v0.1 support structured output / JSON mode?
No. EVA-LLaMA-3.33-70B-v0.1 does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.
Can EVA-LLaMA-3.33-70B-v0.1 accept image input?
No. EVA-LLaMA-3.33-70B-v0.1 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is EVA-LLaMA-3.33-70B-v0.1 open-weight?
No. EVA-LLaMA-3.33-70B-v0.1 is a proprietary model — only Meta (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to EVA-LLaMA-3.33-70B-v0.1?
If EVA-LLaMA-3.33-70B-v0.1 doesn't fit, consider Meta-Llama-3.1-8B-Instruct, Llama-3.3-70B-Instruct, Llama 4 Maverick 17B 128E Instruct FP8. Each one targets the same use case — see the Related links below for direct head-to-head pages.
Where does this data come from?
All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
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- Llama 4 Maverick 17B 128E Instruct FP8$0.14 in / $0.59 out
- Llama 4 Scout 17B 16E Instruct$0.08 in / $0.30 out
- Meta-Llama-3.1-70B-Instruct$0.40 in / $0.40 out
Last updated:
Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.