Skip to content
ModelCap

Head-to-head comparison

DeepSeek V4 Pro 0813 vs GPT-5.5

DeepSeek V4 Pro 0813 (DeepSeek) and GPT-5.5 (OpenAI) compared on the ModelCap Index, API price, context window, provider availability, weight access and every public benchmark board they share. Figures are the same ones shown on the live rankings; nothing here is a hidden score.

Snapshot as of 9 September 2026

As of 9 September 2026, GPT-5.5 holds the stronger ModelCap Index position (#9 vs #20); DeepSeek V4 Pro 0813 is 17.3× cheaper per output token ($1.74/1M vs $30.00/1M); and DeepSeek V4 Pro 0813 ships open weights.

Which should you choose?

Choose DeepSeek V4 Pro 0813 if…

  • API cost matters — $1.74/1M output tokens against $30.00/1M, about 17.3× cheaper.
  • your workload is prompt-heavy — input tokens cost $0.579/1M against $5.00/1M.
  • you want to self-host: DeepSeek V4 Pro 0813 ships open weights while GPT-5.5 is api only.
  • you want provider choice — 19 listed API providers against 3.
  • you want the more recently listed model — DeepSeek V4 Pro 0813 was listed 12 August 2026, GPT-5.5 24 April 2026.

Choose GPT-5.5 if…

  • you want the stronger overall ModelCap Index position — #9 against #20 (79.8 vs 73.6 points).
  • Arena coding is your yardstick — 1520 against 1505.
  • ARC-AGI-2 is your yardstick — 85.0% against 61.3%.
  • AA Intelligence Index is your yardstick — 38.6 against 36.3.
  • AA Terminal-Bench 2.1 is your yardstick — 84.3% against 78.7%.
  • AA Humanity's Last Exam is your yardstick — 45.8% against 41.0%.

DeepSeek V4 Pro 0813 vs GPT-5.5: specs, pricing and context

Specification comparison of DeepSeek V4 Pro 0813 and GPT-5.5
FieldDeepSeek V4 Pro 0813DeepSeekGPT-5.5OpenAI
ModelCap Index position#20#9
Index score73.679.8
EvidenceMeasuredMeasured
Input price / 1M tokens$0.579$5.00
Output price / 1M tokens$1.74$30.00
Context window1M tokens1M tokens
Max output tokens393K128K
API providers listed193
Weight accessOpen weightsAPI only
Input modalitiesTextFile, Image, Text
First listed12 August 202624 April 2026
PublisherDeepSeekOpenAI

Evidence: 4 public benchmark observations across 4 boards · 7 public benchmark observations across 7 boards. Prices are the lowest listed API offer per million tokens observed on the OpenRouter catalogue.

Benchmark scores: DeepSeek V4 Pro 0813 vs GPT-5.5

Public benchmark boards where DeepSeek V4 Pro 0813 or GPT-5.5 has a published result
BoardDeepSeek V4 Pro 0813GPT-5.5Leads
Arena codingArena (LMArena)15051490–1519High15201514–1526HighGPT-5.5
LMArena AgentLMArena—5.3%4.3%–6.4%X-HighOnly one result
ARC-AGI-2ARC Prize Foundation61.3%Max85.0%X-HighGPT-5.5
ARC-AGI-3ARC Prize Foundation—0.4%HighOnly one result
AA Intelligence IndexArtificial Analysis36.3intelligence-index:v4.3:max38.6intelligence-index:v4.3:xhighGPT-5.5
AA Terminal-Bench 2.1Artificial Analysis78.7%terminal-bench:2.1:terminus-2:e2b:pass-at-1:3-repeats:source-model="DeepSeek V4 Pro 0813 (max)":reasoning=true84.3%terminal-bench:2.1:terminus-2:e2b:pass-at-1:3-repeats:source-model="GPT-5.5 (xhigh)":reasoning=trueGPT-5.5
AA τ²-Bench TelecomArtificial Analysis—93.9%tau2:telecom:dual-control:pass-at-1:3-repeats:source-model="GPT-5.5 (xhigh)":reasoning=trueOnly one result
AA Humanity's Last ExamArtificial Analysis41.0%hle:may-2025:text-only-2158:no-tools:pass-at-1:source-model="DeepSeek V4 Pro 0813 (max)":reasoning=true45.8%hle:may-2025:text-only-2158:no-tools:pass-at-1:source-model="GPT-5.5 (xhigh)":reasoning=trueGPT-5.5
Terminal-Bench 2.1 Terminus 2Terminal-Bench—78.0X-HighOnly one result
WildClawBench OpenClawWildClawBench—58.2Only one result

Scores are the sources' own published figures for each model's best evaluated configuration; ModelCap never re-runs a benchmark.

Want a different pairing? Open the interactive comparison tool to swap either model for any current ranked language model.

DeepSeek V4 Pro 0813 vs GPT-5.5: common questions

Is DeepSeek V4 Pro 0813 better than GPT-5.5?

GPT-5.5 ranks higher on the ModelCap Index as of 9 September 2026: #9 against #20. That is a capability ranking built from public benchmark evidence with published uncertainty; whether it is "better" for you also depends on price, context and where you can run it. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.

Is DeepSeek V4 Pro 0813 cheaper than GPT-5.5?

DeepSeek V4 Pro 0813 is cheaper on output tokens: $1.74/1M against $30.00/1M. Input tokens are $0.579/1M for DeepSeek V4 Pro 0813 and $5.00/1M for GPT-5.5. Prices are the lowest listed API offer ModelCap observed, in USD per million tokens. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $2.03 for DeepSeek V4 Pro 0813 versus $25.00 for GPT-5.5. DeepSeek V4 Pro 0813 costs 91.9% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.

Which has the bigger context window, DeepSeek V4 Pro 0813 or GPT-5.5?

Both publish a 1M-token context window.

Which is better for coding, DeepSeek V4 Pro 0813 or GPT-5.5?

Arena coding: DeepSeek V4 Pro 0813 1505, GPT-5.5 1520 — GPT-5.5 leads. AA Terminal-Bench 2.1: DeepSeek V4 Pro 0813 78.7%, GPT-5.5 84.3% — GPT-5.5 leads.

Are DeepSeek V4 Pro 0813 and GPT-5.5 open-weight models?

DeepSeek V4 Pro 0813: Open weights. GPT-5.5: API only. Open weights mean the checkpoint can be downloaded and self-hosted under its licence; API-only models are available solely through hosted endpoints.

Where can I run DeepSeek V4 Pro 0813 and GPT-5.5?

ModelCap currently lists 19 API providers for DeepSeek V4 Pro 0813 and 3 for GPT-5.5, from the OpenRouter catalogue snapshot the site serves; each model page lists the providers and their prices.

How current is this DeepSeek V4 Pro 0813 vs GPT-5.5 comparison?

Every figure comes from the sealed ModelCap dataset published 9 September 2026; the page re-renders within a minute of each data refresh, and the ModelCap Index positions are the same ones shown on the live rankings.

Explore further