Deepseek V3 Review - Everything You Need to Know

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Gemini 2.5 Pro is Google DeepMind’s advanced hybrid-reasoning AI model, designed to think deeply before responding. With support for multimodal inputs—text, images, audio, video, and code—it offers lightning-fast inference performance, up to 2 million tokens of context, and top-tier results in math, science, and coding benchmarks.

Gemini 2.5 Pro

18

Gemini 2.5 Pro is Google DeepMind’s advanced hybrid-reasoning AI model, designed to think deeply before responding. With support for multimodal inputs—text, images, audio, video, and code—it offers lightning-fast inference performance, up to 2 million tokens of context, and top-tier results in math, science, and coding benchmarks.

Gemini 2.5 Pro

18

Gemini 2.5 Pro is Google DeepMind’s advanced hybrid-reasoning AI model, designed to think deeply before responding. With support for multimodal inputs—text, images, audio, video, and code—it offers lightning-fast inference performance, up to 2 million tokens of context, and top-tier results in math, science, and coding benchmarks.

Gemini 1.5 Pro

12

Gemini 1.5 Pro is Google DeepMind’s mid-size multimodal model, using a mixture-of-experts (MoE) architecture to deliver high performance with lower compute. It supports text, images, audio, video, and code, and features an experimental context window up to 1 million tokens—the longest among widely available models. It excels in long-document reasoning, multimodal understanding, and in-context learning.

Gemini 1.5 Pro

12

Gemini 1.5 Pro is Google DeepMind’s mid-size multimodal model, using a mixture-of-experts (MoE) architecture to deliver high performance with lower compute. It supports text, images, audio, video, and code, and features an experimental context window up to 1 million tokens—the longest among widely available models. It excels in long-document reasoning, multimodal understanding, and in-context learning.

Gemini 1.5 Pro

12

Gemini 1.5 Pro is Google DeepMind’s mid-size multimodal model, using a mixture-of-experts (MoE) architecture to deliver high performance with lower compute. It supports text, images, audio, video, and code, and features an experimental context window up to 1 million tokens—the longest among widely available models. It excels in long-document reasoning, multimodal understanding, and in-context learning.

Janus-Pro-7B

10

anus Pro 7B is DeepSeek’s flagship open-source multimodal AI model, unifying vision understanding and text-to-image generation within a single transformer architecture. Built on DeepSeek‑LLM‑7B, it uses a decoupled visual encoding approach paired with SigLIP‑L and VQ tokenizer, delivering superior visual fidelity, prompt alignment, and stability across tasks—benchmarked ahead of OpenAI’s DALL‑E 3 and Stable Diffusion variants.

Janus-Pro-7B

10

anus Pro 7B is DeepSeek’s flagship open-source multimodal AI model, unifying vision understanding and text-to-image generation within a single transformer architecture. Built on DeepSeek‑LLM‑7B, it uses a decoupled visual encoding approach paired with SigLIP‑L and VQ tokenizer, delivering superior visual fidelity, prompt alignment, and stability across tasks—benchmarked ahead of OpenAI’s DALL‑E 3 and Stable Diffusion variants.

Janus-Pro-7B

10

anus Pro 7B is DeepSeek’s flagship open-source multimodal AI model, unifying vision understanding and text-to-image generation within a single transformer architecture. Built on DeepSeek‑LLM‑7B, it uses a decoupled visual encoding approach paired with SigLIP‑L and VQ tokenizer, delivering superior visual fidelity, prompt alignment, and stability across tasks—benchmarked ahead of OpenAI’s DALL‑E 3 and Stable Diffusion variants.

grok-3-fast

Grok 3 Fast is xAI’s low-latency variant of their flagship Grok 3 model. It delivers identical output quality but responds faster by leveraging optimized serving infrastructure—ideal for real-time, speed-sensitive applications. It inherits the same multimodal, reasoning, and chain-of-thought capabilities as Grok 3, with a large context window of ~131K tokens.

grok-3-fast

Grok 3 Fast is xAI’s low-latency variant of their flagship Grok 3 model. It delivers identical output quality but responds faster by leveraging optimized serving infrastructure—ideal for real-time, speed-sensitive applications. It inherits the same multimodal, reasoning, and chain-of-thought capabilities as Grok 3, with a large context window of ~131K tokens.

grok-3-fast

Grok 3 Fast is xAI’s low-latency variant of their flagship Grok 3 model. It delivers identical output quality but responds faster by leveraging optimized serving infrastructure—ideal for real-time, speed-sensitive applications. It inherits the same multimodal, reasoning, and chain-of-thought capabilities as Grok 3, with a large context window of ~131K tokens.

grok-3-fast-latest

Grok 3 Fast is xAI’s speed-optimized variant of their flagship Grok 3 model, offering identical output quality with lower latency. It leverages the same underlying architecture—including multimodal input, chain-of-thought reasoning, and large context—but serves through optimized infrastructure for real-time responsiveness. It supports up to 131,072 tokens of context.

grok-3-fast-latest

Grok 3 Fast is xAI’s speed-optimized variant of their flagship Grok 3 model, offering identical output quality with lower latency. It leverages the same underlying architecture—including multimodal input, chain-of-thought reasoning, and large context—but serves through optimized infrastructure for real-time responsiveness. It supports up to 131,072 tokens of context.

grok-3-fast-latest

Grok 3 Fast is xAI’s speed-optimized variant of their flagship Grok 3 model, offering identical output quality with lower latency. It leverages the same underlying architecture—including multimodal input, chain-of-thought reasoning, and large context—but serves through optimized infrastructure for real-time responsiveness. It supports up to 131,072 tokens of context.

Meta Llama 4 Scout

5

2

Llama 4 Scout is Meta’s compact and high-performance entry in the Llama 4 family, released April 5, 2025. Built on a mixture-of-experts (MoE) architecture with 17B active parameters (109B total) and a staggering 10‑million-token context window, it delivers top-tier speed and long-context reasoning while fitting on a single Nvidia H100 GPU. It outperforms models like Google's Gemma 3, Gemini 2.0 Flash‑Lite, and Mistral 3.1 across benchmarks.

Meta Llama 4 Scout

5

2

Llama 4 Scout is Meta’s compact and high-performance entry in the Llama 4 family, released April 5, 2025. Built on a mixture-of-experts (MoE) architecture with 17B active parameters (109B total) and a staggering 10‑million-token context window, it delivers top-tier speed and long-context reasoning while fitting on a single Nvidia H100 GPU. It outperforms models like Google's Gemma 3, Gemini 2.0 Flash‑Lite, and Mistral 3.1 across benchmarks.

Meta Llama 4 Scout

5

2

Llama 4 Scout is Meta’s compact and high-performance entry in the Llama 4 family, released April 5, 2025. Built on a mixture-of-experts (MoE) architecture with 17B active parameters (109B total) and a staggering 10‑million-token context window, it delivers top-tier speed and long-context reasoning while fitting on a single Nvidia H100 GPU. It outperforms models like Google's Gemma 3, Gemini 2.0 Flash‑Lite, and Mistral 3.1 across benchmarks.

Llama 4 Maverick is Meta’s powerful mid-sized model in the Llama 4 series, released April 5, 2025. Built with a mixture-of-experts (MoE) architecture featuring 17 B active parameters (out of 400 B total) and 128 experts, it supports a 1 million-token context window and native multimodality for text and image inputs. It ranks near the top of competitive benchmarks—surpassing GPT‑4o and Gemini 2.0 Flash in reasoning, coding, and visual tasks.

Llama 4 Maverick is Meta’s powerful mid-sized model in the Llama 4 series, released April 5, 2025. Built with a mixture-of-experts (MoE) architecture featuring 17 B active parameters (out of 400 B total) and 128 experts, it supports a 1 million-token context window and native multimodality for text and image inputs. It ranks near the top of competitive benchmarks—surpassing GPT‑4o and Gemini 2.0 Flash in reasoning, coding, and visual tasks.