ZMIME
Comparison · 3 models · Updated Oct 4, 2026

DeepSeek V3.2 vs DeepSeek V3 0324 vs GPT-5.4 nano

GPT-5.4 nano comes out ahead, 68 to 64 and 54 on our weighted score, though DeepSeek V3.2 is 26% cheaper per token.

  1. DeepSeek

    DeepSeek V3.2

    Released Dec 1, 2025

    64/100
    • ECI146.3
    • Price$0.296 / $0.48
    • Context128K
  2. DeepSeek

    DeepSeek V3 0324

    Released Mar 24, 2025

    54/100
    • ECI135.9
    • Price$0.24 / $0.90
    • Context164K
  3. Our pick

    OpenAI

    GPT-5.4 nano

    Released Mar 17, 2026

    68/100
    • ECI145.8
    • Price$0.20 / $1.25
    • Context400K
01 — Verdict

GPT-5.4 nano is our pick

GPT-5.4 nano is the better all-round choice, scoring 68/100 against DeepSeek V3.2 (64) and DeepSeek V3 0324 (54). It leads on inputs & features and context window. DeepSeek V3.2 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityDeepSeek V3.2Capabilities Index (ECI): DeepSeek V3.2 146.3 · GPT-5.4 nano 145.8 · DeepSeek V3 0324 135.9
  • Lowest priceDeepSeek V3.2DeepSeek V3.2 $0.342 · DeepSeek V3 0324 $0.405 · GPT-5.4 nano $0.463 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.4 nanoGPT-5.4 nano 400,000 · DeepSeek V3 0324 163,840 · DeepSeek V3.2 128,000 tokens
  • Widest inputsGPT-5.4 nanoDeepSeek V3.2: Text · DeepSeek V3 0324: Text · GPT-5.4 nano: Text, Images
  • Self-hostingDeepSeek V3.2 and DeepSeek V3 0324Publishes downloadable weights (MIT License)
How the score is built
MeasureWeightDeepSeek V3.2DeepSeek V3 0324GPT-5.4 nano
CapabilityCapabilities Index (ECI)50%736073
Price25%726866
Inputs & features15%452570
Context window10%242844
Overall100%64/10054/10068/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

DeepSeek V3.2 vs DeepSeek V3 0324 vs GPT-5.4 nano specifications side by side
SpecificationDeepSeek V3.2DeepSeekDeepSeek V3 0324DeepSeekGPT-5.4 nanoOpenAI
Capability
Capabilities Index (ECI)146.3 (best)135.9145.8
ECI rank#69 of 148 (best)#114 of 148#75 of 148
GPQA DiamondGraduate-level science questions83.4% (best)67.6%78.5%
FrontierMath Tiers 1–3Research-level mathematics——44.9%
OTIS Mock AIME 2024–2025Competition mathematics87.8% (best)37.8%87.8%
SimpleQA VerifiedShort factual questions——11.7%
Price per million tokens
Input$0.296$0.24$0.20 (best)
Output$0.48 (best)$0.90$1.25
Cached input——$0.02
Blended (3:1)$0.342 (best)$0.405$0.463
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 15 providersMedian of 5 providersOfficial OpenAI API
Limits
Context window128,000 tokens163,840 tokens400,000 tokens (best)
Max output64,000 tokens163,840 tokens (best)128,000 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoYeslow · medium · high · xhigh
Tool callingYesYesYes
Structured outputYesNoYes
Availability
WeightsOpenMIT LicenseOpenProprietary
API model ID——gpt-5.4-nano
API providers15526 (best)
ReleasedDec 1, 2025Mar 24, 2025Mar 17, 2026
Knowledge cutoffJul 2024—Aug 31, 2025
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • DeepSeek V3.2$3.92
  • DeepSeek V3 0324$4.20
  • GPT-5.4 nano$4.50
04 — Questions

Which should you choose?

Which is better: DeepSeek V3.2, DeepSeek V3 0324 or GPT-5.4 nano?

GPT-5.4 nano is the better all-round choice, scoring 68/100 against DeepSeek V3.2 (64) and DeepSeek V3 0324 (54). It leads on inputs & features and context window. DeepSeek V3.2 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek V3.2, DeepSeek V3 0324 or GPT-5.4 nano?

DeepSeek V3.2 is cheaper at $0.296 input / $0.48 output per million tokens (median across 15 API providers). DeepSeek V3 0324 costs $0.24 input / $0.90 output per million tokens (median across 5 API providers); GPT-5.4 nano costs $0.20 input / $1.25 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.342 per million tokens for DeepSeek V3.2 versus $0.405 for DeepSeek V3 0324 (1.2× as much) and $0.463 for GPT-5.4 nano (1.4× as much).

Which scores higher on benchmarks?

DeepSeek V3.2 scores higher on the Capabilities Index (ECI): DeepSeek V3.2 146.3 (#69 of 148), GPT-5.4 nano 145.8 (#75 of 148) and DeepSeek V3 0324 135.9 (#114 of 148). The confidence ranges of the top two overlap (144.4–147.5 vs 143.2–147.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek V3.2 83.4%, GPT-5.4 nano 78.5%, DeepSeek V3 0324 67.6%; OTIS Mock AIME 2024–2025 — DeepSeek V3.2 87.8%, GPT-5.4 nano 87.8%, DeepSeek V3 0324 37.8%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek V3.2, DeepSeek V3 0324 and GPT-5.4 nano yet, so there is no like-for-like coding score. On overall capability, DeepSeek V3.2 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

GPT-5.4 nano has the largest context window at 400,000 tokens, against 163,840 for DeepSeek V3 0324 and 128,000 for DeepSeek V3.2. Maximum output per response: DeepSeek V3.2 up to 64,000, DeepSeek V3 0324 up to 163,840, GPT-5.4 nano up to 128,000 tokens.

Which can read images, PDFs, audio or video?

DeepSeek V3.2 accepts text; DeepSeek V3 0324 accepts text; GPT-5.4 nano accepts text and images. GPT-5.4 nano handles the widest range of inputs.

Are any of these open source?

DeepSeek V3.2 and DeepSeek V3 0324 publishes its weights (MIT License) and can be self-hosted; GPT-5.4 nano is proprietary.

Which is newer?

GPT-5.4 nano is the newest, released Mar 17, 2026. DeepSeek V3.2 came out Dec 1, 2025; DeepSeek V3 0324 came out Mar 24, 2025. Knowledge cutoff: DeepSeek V3.2 Jul 2024, GPT-5.4 nano Aug 31, 2025.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.