DeepSeek V4 Pro Alternatives: Exploring Available Options

GLM-5.3-Flash from Z.ai provides an MIT-licensed 320B parameter MoE architecture that activates only 18B parameters per token, paired with native video, image, text, and file ingestion. At an API baseline of $0.15 per million input tokens and $0.50 per million output tokens, it offers a remarkably affordable managed endpoint, while the model card documents six separate serving frameworks including vLLM, SGLang, and KTransformers alongside 115 quantisations for lightweight self-hosting.

Best for: Engineering teams that require fully open MIT weights, native visual and video ingestion, and very low hosted token rates.

Consider: Although marketed with a 1M-token context window, the model card notes evaluation at a 300,000-token maximum context length with a context management strategy, and its documentation does not publish a latency figure or fixed knowledge cutoff.

MiniMax-M3 is a 428B open-weight mixture-of-experts model activating roughly 23B parameters per token, trained with native multimodal support covering text, image, and video. It introduces an adaptive thinking parameter that lets the model independently assess whether a request requires extra reasoning, alongside an explicit disabled state to maximize raw inference throughput and minimize latency.

Best for: Workflows requiring native video understanding and dynamic, request-level control over whether reasoning tokens are spent.

Consider: The weights are released under the custom MiniMax Community licence rather than standard MIT, and API token pricing doubles for requests that exceed 512K input tokens.

GPT-6 Astra is OpenAI's flagship hosted model engineered for long-horizon agentic workflows, complex reasoning, and computer use. It features a 1,050,000-token context window, a 128,000-token maximum output limit, five distinct reasoning-effort levels from low to max, and built-in execution tools such as hosted shell and patch application, backed by a published knowledge cutoff of 30 April 2026.

Best for: Organizations needing autonomous agentic tooling, native computer use execution, and managed cloud infrastructure without operational self-hosting duties.

Consider: It is entirely closed-source with no self-hosted option, costs $10.00 per million input tokens at standard rates, doubles to $20.00 for long-context queries, and has fast mode disabled under EU data residency.

Moonshot's Kimi K3 delivers a massive 2.8T MoE architecture with 104B active parameters per token, achieving an 88.3 score on Terminal-Bench 2.1 and 91.2 on BrowseComp. It provides a 1,048,576-token context window, incorporates a 401M-parameter vision encoder for native image and video ingestion, and ships with quantisation-aware trained MXFP4 weights for serving via vLLM, SGLang, or TokenSpeed.

Best for: Teams tackling complex browser or terminal-based agent tasks that prioritize high benchmarked problem solving and quantisation-ready open weights.

Consider: Thinking is always active and cannot be switched off, meaning every request incurs reasoning token generation at the $15.00 per million output token rate, and the weights are governed by a custom Kimi K3 License.

Mistral Medium 3.5 unifies coding, reasoning, and instruction following into a dense 128B architecture distributed under a Modified MIT License. It accepts text and image inputs, provides a dated release version (v26.04) with an official lifecycle policy, and supports straightforward local deployment across runtimes like vLLM, llama.cpp, and LM Studio.

Best for: Teams seeking a dense, easily deployable model with a predictable lifecycle and simple per-request reasoning toggles between none and high.

Consider: The context window is capped at 256K tokens, and the Modified MIT License incorporates an unspecified exemption for companies with large revenue that requires commercial review.

Claude Fable 5.1 is Anthropic's dedicated model for demanding multistep reasoning and long-running agentic tasks across code and enterprise documents. It features a 1M-token context window, a 128K output capacity, and broad enterprise cloud availability across the Claude API, AWS, Google Cloud, and Microsoft Foundry, coupled with aggressive prompt caching priced at $0.25 per million tokens.

Best for: Enterprises prioritizing deep agentic reasoning across major cloud ecosystems with formal retirement commitments and cost-effective prompt cache reads.

Consider: The model has no open weights, runs at slower comparative latency, incurs premium pricing of $10.00 in and $50.00 out per million tokens, and enforces always-on adaptive thinking while returning an error on forced tool choice.