DeepSeek V3.2 vs Grok 4.3

Pricing math on a real workload

On OpenKey, DeepSeek V3.2 costs 0.235664 per 1M input tokens (0.2288 x 1.03) and 0.353496 per 1M output tokens (0.3432 x 1.03). Grok 4.3 costs 1.2875 per 1M input (1.25 x 1.03) and 2.575 per 1M output (2.5 x 1.03). Run the numbers on a 10M-input / 2M-output workload and DeepSeek V3.2 comes out to 2.97 total, while Grok 4.3 lands at 17.50 — nearly 6x more for the same token counts. If your app is a high-throughput pipeline (batch summarization, RAG over large corpora, agent loops with lots of tool calls), that gap compounds fast across a billing cycle. Grok's cache-read rate (0.2/1M provider price) is cheaper than its fresh-input rate, which helps if your prompts reuse a large system context, but it still doesn't close the gap with V3.2's base pricing.

Context window: 131K vs 1M

Grok 4.3 ships a 1,000,000-token context window, DeepSeek V3.2 tops out at 131,072 — a ratio of about 0.13. That difference matters for anything involving whole codebases, long legal or research documents, or multi-hour conversation history in a single call. V3.2's max completion is capped at 64,000 tokens; Grok 4.3's max output isn't capped in the same way in this data. If your workload needs to hold an entire repo or a long document set in context without chunking, Grok 4.3 is the only one of the two that can do it in a single pass.

Design Arena benchmark comparison

Across every shared model category — 3d, asciiart, codecategories, dataviz, gamedev, svg, uicomponent, website — Grok 4.3 outscores DeepSeek V3.2 on elo. Examples: uicomponent (1250 vs 1203), website (1244 vs 1217), gamedev (1242 vs 1197), codecategories (1243 vs 1213), dataviz (1234 vs 1203), asciiart (1189 vs 1129), 3d (1202 vs 1210 — the one category where V3.2 edges ahead), svg (1140 vs 1089). Grok 4.3 also has agent-arena scores (webapps elo 1194, rank 14; mobileapps elo 1146, rank 26) that V3.2 has no equivalent data for in this set. Grok's artificial_analysis scores: intelligence_index 37.6, coding_index 42.2, agentic_index 24.1 — no comparable artificial_analysis numbers exist for V3.2 here, so treat that as a Grok-only data point, not a head-to-head.

Modality and tool support

DeepSeek V3.2 is text-in, text-out only. Grok 4.3 accepts text, image, and file input and outputs text — useful if your app needs to read screenshots, PDFs, or scanned documents alongside prompts. On tool-calling parameters, V3.2 supports more knobs (frequency_penalty, min_p, top_k, logit_bias, structured_outputs among 19 total params) versus Grok 4.3's 14. Grok 4.3 defaults to reasoning enabled (default_effort: low, with high/medium/low/none available); V3.2's reasoning is optional and off by default. If you need explicit control over reasoning depth per call, Grok 4.3's effort levels give you that dial.

Questions

How much cheaper is DeepSeek V3.2 than Grok 4.3?

On OpenKey, DeepSeek V3.2 input tokens cost 0.235664 per 1M versus Grok 4.3's 1.2875 per 1M — about 5.5x cheaper. On a 10M-input/2M-output workload the total cost is 2.97 for V3.2 versus 17.50 for Grok 4.3.

Which model has a bigger context window?

Grok 4.3 supports 1,000,000 tokens of context, DeepSeek V3.2 supports 131,072 — a ratio of roughly 0.13. If you need to process very long documents or full codebases in one call, Grok 4.3 is the only option of the two.

Does DeepSeek V3.2 support image input?

No. DeepSeek V3.2 is text-to-text only. Grok 4.3 accepts text, image, and file inputs and outputs text, making it the choice for any workload involving screenshots or document scans.

Which model wins on Design Arena benchmarks?

Grok 4.3 leads in nearly every shared category — uicomponent (1250 vs 1203 elo), website (1244 vs 1217), gamedev (1242 vs 1197). DeepSeek V3.2 only leads in the 3d category, 1210 vs 1202.