Titan Text Embeddings V2
vercel/titan-embed-text-v2من vercel · العائلة: titan-embed · أُصدِر 2024-04
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
القدرات
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
Agents1
- Tool calling0/35
- Structured output0/25
- Reasoning0/15
- Output token limit0/15
- Provider availability1/10
JSON / structured output20
- Structured output / JSON mode0/50
- Tool calling0/20
- Temperature control0/10
- Price-friendly for high-volume20/20
Cost efficiency95
- Headline price (log-scaled)95/95
- 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 | $0.10 < $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 | $0.20 < $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 | $0.04 < $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 | $0.16 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $0.24 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
تفاصيل التسعير
السعر المُوصى به من vercel · amazon/titan-embed-text-v2
متاح لدى 1 مزود
| المزود | معرف نموذج المزود | إدخال / 1M | إخراج / 1M | السياق | تاريخ الإصدار |
|---|---|---|---|---|---|
| Vercel AI Gateway vercel | amazon/titan-embed-text-v2 | $0.020 | Unknown | 8K | 2024-04 |
Frequently asked questions
How much does Titan Text Embeddings V2 cost?
Titan Text Embeddings V2 costs $0.020 per 1M input tokens and Unknown per 1M output tokens, sourced from vercel. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Titan Text Embeddings V2?
Titan Text Embeddings V2 has a context window of 8K tokens, with a max output of 2K tokens per reply. This is the total combined size of prompt + completion.
Does Titan Text Embeddings V2 support tool calling?
No. Titan Text Embeddings V2 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does Titan Text Embeddings V2 support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Titan Text Embeddings V2 in our data source. Verify with vercel's official documentation before relying on it in production.
Can Titan Text Embeddings V2 accept image input?
No. Titan Text Embeddings V2 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Titan Text Embeddings V2 open-weight?
No. Titan Text Embeddings V2 is a proprietary model — only vercel (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to Titan Text Embeddings V2?
If Titan Text Embeddings V2 doesn't fit, consider Trinity Mini, Trinity Large Thinking, Trinity Large Preview. 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
More vercel models
- Trinity Mini$0.05 in / $0.15 out
- Trinity Large Thinking$0.25 in / $0.90 out
- Trinity Large Preview$0.25 in / $1.00 out
- INTELLECT 3$0.20 in / $1.10 out
- Nova 2 Lite$0.30 in / $2.50 out
آخر تحديث:
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.