Gemini 1.5 Pro
Google's long-context multimodal model with up to 2M token windows.
- Context
- 2M
- Max output
- 8.2K
- Input / 1M
- $1.25
- Output / 1M
- $5.00
- Output speed
- 65 t/s
Accepts
- Text input
- Image input
- Audio input
- Video input
Produces
- Text output
AI model comparison
Compare recorded price, context, output limits, speed, latency, capabilities, and input/output support. Every missing value stays visible, and unsourced benchmarks are excluded.
This Gemini 1.5 Pro vs Phi 4 comparison is designed for teams choosing between two production model records, not for declaring a universal winner. Gemini 1.5 Pro by Google currently records 2M context, 8.2K maximum output, $1.25 input per 1M tokens, $5.00 output per 1M tokens, 65 t/s recorded output speed, 0.90s recorded time to first token. Phi 4 by Deepinfra via Requesty records 16.4K context, $0.07 input per 1M tokens, $0.14 output per 1M tokens. The tables below separate documented capabilities, commercial limits, directory measurements, and source-linked benchmark evidence so you can see where the data is complete and where independent testing is still required.
Google's long-context multimodal model with up to 2M token windows.
Accepts
Produces
Deepinfra via Requesty
Phi-4-reasoning-plus is an enhanced 14B parameter model from Microsoft, fine-tuned from Phi-4 with additional reinforcement learning to boost accuracy on math, science, and code reasoning tasks. It uses the same dense decoder-only transformer architecture as Phi-4, but generates longer, more comprehensive outputs structured into a step-by-step reasoning trace and final answer. While it offers improved benchmark scores over Phi-4-reasoning across tasks like AIME, OmniMath, and HumanEvalPlus, its responses are typically ~50% longer, resulting in higher latency. Designed for English-only applications, it is well-suited for structured reasoning workflows where output quality takes priority over response speed.
Accepts
Produces
At a glance
This is a directional summary of the values recorded in this directory—not a universal quality verdict. Test the finalists on your own prompts before committing.
Where Gemini 1.5 Pro leads in recorded data
Where Phi 4 leads in recorded data
Context capacity
Higher listed limit
Gemini 1.5 Pro:2M
Phi 4:16.4K
Gemini 1.5 Pro
Maximum output
Higher listed limit
Gemini 1.5 Pro:8.2K
Phi 4:—
No complete comparison
Input price
Lower recorded price
Gemini 1.5 Pro:$1.25
Phi 4:$0.07
Phi 4
Output price
Lower recorded price
Gemini 1.5 Pro:$5.00
Phi 4:$0.14
Phi 4
Output speed
Higher recorded throughput
Gemini 1.5 Pro:65 t/s
Phi 4:—
No complete comparison
Time to first token
Lower recorded latency
Gemini 1.5 Pro:0.90s
Phi 4:—
No complete comparison
Intelligence Index
Higher directory index
Gemini 1.5 Pro:75.8
Phi 4:—
No complete comparison
Evidence
A score appears only when both records include a verified source. It is not treated as a universal ranking.
Specifications
| Specification | Gemini 1.5 Pro | Phi 4 |
|---|---|---|
| Provider | Deepinfra via Requesty | |
| Model family | Gemini 1.5 | — |
| Accepted inputs | text, image, audio, video | text |
| Produced outputs | text | text |
| Context window | 2MRecorded lead | 16.4K |
| Max output | 8.2K | — |
| Intelligence Index | 75.8 | — |
| Input price / 1M | $1.25 | $0.07Recorded lead |
| Output price / 1M | $5.00 | $0.14Recorded lead |
| Output speed | 65 t/s | — |
| Time to first token | 0.90s | — |
| Reasoning mode | Not documented | Not documented |
| Tool calling | Documented | Not documented |
| Image input | Documented | Not documented |
| Audio input | Documented | Not documented |
| Structured output | Documented | Documented |
| License | Proprietary | Not documented |
| Released | May 14, 2024 | Not documented |
Workload guidance
Gemini 1.5 Pro currently leads on larger context. Phi 4 currently leads on lower recorded input price, lower recorded output price. Choose according to the constraints that matter to your workload, then run the same representative prompts against both models before making a production commitment. Neither the larger number nor the lower price is automatically the better choice: prompt quality, tool reliability, modality support, rate limits, data policy, and provider implementation can change the result. Use this page to build a shortlist, confirm current terms in the linked sources, and validate quality, latency, and cost with your own traffic.
Provenance
Prices and hosted performance can change. SyncDev records source references and clearly separates documented specifications from measured values; confirm commercial terms with the provider before deployment.
Gemini 1.5 Pro
Google · model record and recorded source
Phi 4
Deepinfra via Requesty · model record and recorded source
Choose any two approved model records and review them with the same evidence rules.