Gemini 2.0 Pro 1206
nano-gpt/gemini-exp-1206Par nano-gpt · sorti 2024-12-06
⚠ Il s'agit d'un fine-tune communautaire ou dérivé — pas d'une publication officielle de l'éditeur.
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capacités
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.
Coding21
- Tool calling0/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)20/20
- Provider availability1/10
Agents6
- Tool calling0/35
- Structured output0/25
- Reasoning0/15
- Output token limit5/15
- Provider availability1/10
JSON / structured output7
- Structured output / JSON mode0/50
- Tool calling0/20
- Temperature control0/10
- Price-friendly for high-volume7/20
Cost efficiency43
- Headline price (log-scaled)43/95
- Has prompt-cache pricing0/5
Long context100
- Context window (100K → 2M)90/90
- Has published price for full window10/10
Vision91
- Accepts image input50/50
- Context window (10K → 1M)30/30
- Has published price10/10
- Provider availability1/10
Production-readiness50
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers10/10
- Official model (not derivative)0/15
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 | $8.79 < $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 | $17.58 < $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 | $5.02 < $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 | $15.06 $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 | $18.09 $0.02 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Détail des tarifs
Tarif recommandé de nano-gpt · gemini-exp-1206
Disponible chez 1 fournisseurs
| Fournisseur | ID modèle fournisseur | Entrée / 1M | Sortie / 1M | Contexte | Publié le |
|---|---|---|---|---|---|
| NanoGPT nano-gpt | gemini-exp-1206 | $1.26 | $5.00 | 2.10M | 2024-12-06 |
Frequently asked questions
How much does Gemini 2.0 Pro 1206 cost?
Gemini 2.0 Pro 1206 costs $1.26 per 1M input tokens and $5.00 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 Gemini 2.0 Pro 1206?
Gemini 2.0 Pro 1206 has a context window of 2.10M tokens, with a max output of 8K tokens per reply. This is the total combined size of prompt + completion.
Does Gemini 2.0 Pro 1206 support tool calling?
No. Gemini 2.0 Pro 1206 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does Gemini 2.0 Pro 1206 support structured output / JSON mode?
No. Gemini 2.0 Pro 1206 does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.
Can Gemini 2.0 Pro 1206 accept image input?
Yes. Gemini 2.0 Pro 1206 accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check nano-gpt's docs for the exact rule.
Is Gemini 2.0 Pro 1206 open-weight?
No. Gemini 2.0 Pro 1206 is a proprietary model — only nano-gpt (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to Gemini 2.0 Pro 1206?
If Gemini 2.0 Pro 1206 doesn't fit, consider Brave (Answers), Exa (Research), Auto model (Basic). 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 nano-gpt models
- Brave (Answers)$5.00 in / $5.00 out
- Exa (Research)$2.50 in / $2.50 out
- Auto model (Basic)$10.00 in / $19.99 out
- Jamba Mini$0.20 in / $0.41 out
- Yi Large$3.20 in / $3.20 out
Capability lists this model is in
Dernière mise à jour :
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.