Gemini 4 Carbon
gemini-4-carbonCompare gemini-4-carbon API pricing, supported endpoints, capabilities and access options on Modelsell.
- Starting price
- Input / Output · 1M
- Context
- 1M
- Maximum input window
- Max output
- 65.5K
- Maximum tokens per response
- Modalities
- →
- Released
- Nov 2026
Pricing by Supplier
Compare prices and service performance for this model across suppliers.
| Supplier | Discount | Input/M | Output/M | Cache Read/M | ||||
|---|---|---|---|---|---|---|---|---|
Google AI Studio 谷歌官方接口 | -50% | $1 | $5 | $0.05 | ||||
Google Vertex 谷歌官方接口 | -30% | $1.4 | $7 | $0.07 |
Scroll horizontally to compare all prices and performance metrics.
Capabilities / Supported modalities
Provider & data privacy
SentencePiece (Gemini)Performance
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·Gemini 4 Carbon
This model is not included in the current benchmark snapshot.
Missing models or measurements are not zero scores.
Benchmark charts preserve the source model selection and reasoning settings. Missing models or measurements are not zero scores, and benchmark cost or speed is not this site’s service commitment.
About Gemini 4 Carbon
Gemini 4 Carbon 于 2026 年 11 月 10 日通过 Gemini API 正式开放。它适合需要反复验证的复杂编程任务、跨文档分析和数学及科学推理。
输入、思考和输出共享 1,048,576 token 上下文。Google 官方常规同步输出上限为 65,536 token（包含思考）；更长输出需要使用官方长输出流程，且受剩余上下文限制。
Google Gemini API 标准价（美元／百万 token）：截至 2026 年 11 月 30 日，输入 $2.00、输出 $10.00、缓存读取 $0.10；自 2026 年 12 月 1 日起，分别为 $4.00、$20.00、$0.20。输出包含思考 token。只支持隐式缓存。
来源：Google 模型文档 · Google API 发布记录 · Google 官方定价。
Use cases and prompting
适合分析长文档和多媒体材料、定位复杂代码问题，以及整理需要验证的研究结论。可先从官方默认的中等推理档位开始，再按任务复杂度调整。
示例：阅读产品说明 PDF 和演示视频，按功能列出两份材料中互相印证或冲突的地方，并引用页码或时间戳。
实际可用协议、参数和上限以 Modelsell 接入的渠道为准。
API access
API documentation
Code samples
/v1beta/models/gemini-4-carbon:generateContent| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Replace <YOUR_API_KEY> with the API key from your token settings.
Authentication
All requests must include Authorization: Bearer <TOKEN> header. Anthropic-formatted endpoints accept the x-api-key header instead.
Generate tokens from the Tokens page; you can scope them to specific models, groups, IPs, and rate-limits.
Supported parameters
| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Rate limits
| Supplier | RPM | TPM | RPD |
|---|---|---|---|
| Google AI Studio | Unlimited | Unlimited | Unlimited |
| Google Vertex | Unlimited | Unlimited | Unlimited |
No restriction
Frequently asked questions about gemini-4-carbon
What is gemini-4-carbon?
Compare gemini-4-carbon API pricing, supported endpoints, capabilities and access options on Modelsell.
How do I call gemini-4-carbon?
Create an API key with access to gemini-4-carbon, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is gemini-4-carbon priced?
Pricing depends on the selected provider group and the model billing unit. The current input, output, request, or media prices are shown on this page before sign-up.
What is the context window of gemini-4-carbon?
The model catalog lists a context window of 1048576 tokens. Check the selected endpoint for request limits.
What is the maximum output of gemini-4-carbon?
The model catalog lists a maximum output of 65536 tokens. Your request settings may set a lower limit.
How should I evaluate gemini-4-carbon for my project?
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.