MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
Model Comparison · Head to Head

GPT-5.5 vs DeepSeek-V4-Pro

GPT-5.5 wins on Overall, Multimodal; DeepSeek-V4-Pro wins on Coding. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorOpenAI / DeepSeek
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose GPT-5.5 when its stronger dimensions matter most; choose DeepSeek-V4-Pro when lower cost, lower latency is the priority.

Choose GPT-5.5 if you…

  • Balanced with no weak spot
  • Richest ecosystem
  • Mature plugin/function calling
  • Strong creative writing
  • Best for: General tasks, Creative writing, Coding

Choose DeepSeek-V4-Pro if you…

  • Strongest open source
  • Value champion
  • Excellent math reasoning
  • Extremely low price
  • Best for: Coding, Math reasoning, Open-source deployment
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.

GPT-5.5 Higher overall
OpenAI · #5 overall
Overall81
Coding75
Multimodal85
VS
DeepSeek-V4-Pro
DeepSeek · #8 overall
Overall77
Coding79
Multimodal77

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

Specs & pricing — every field side by side

List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.

DimensionGPT-5.5DeepSeek-V4-ProVerdict
VendorOpenAI (US)DeepSeek (CN)Different vendors
Released2026.042026.04DeepSeek-V4-Pro is newer
Overall (rank)81 · #577 · #8GPT-5.5 +4
Coding75 · #879 · #5DeepSeek-V4-Pro +4
Multimodal85 · #877 · #13GPT-5.5 +8
Context window1.05M1MGPT-5.5 larger
Max output128K128KTie
Effective-context9094DeepSeek-V4-Pro more reliable
Input $/1M$5$0.44DeepSeek-V4-Pro cheaper
Output $/1M$30$1.32DeepSeek-V4-Pro cheaper
Cache discount50% offnoneGPT-5.5 deeper
Speed~50 tok/s~70 tok/sDeepSeek-V4-Pro faster
TTFT0.8s0.5sDeepSeek-V4-Pro snappier
Function calling9582GPT-5.5 ahead
Refusal rate~15%~5%DeepSeek-V4-Pro less restrictive
English9482GPT-5.5
Chinese7685DeepSeek-V4-Pro
Modalitiestext, imagetextdifferent coverage
Open weightsNoYesDeepSeek-V4-Pro is open
Fine-tuningYesYes
Free tierChatGPT free tier available (rate-limited); Plus $20/monthDeepSeek App free; new API users receive credits
SOC2 / no-trainyes / yesno / yes
Private deploymentNoYesDeepSeek-V4-Pro

Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

GPT-5.5 leads the overall aggregate by 4 points (81 vs 77). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while DeepSeek-V4-Pro remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a modest gap: DeepSeek-V4-Pro scores 79 against 75. On multi-file edits, SWE-style tickets and long-horizon agent loops DeepSeek-V4-Pro needs fewer correction turns; GPT-5.5 is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

GPT-5.5 leads multimodal 85 vs 77. A concrete modality difference: GPT-5.5 additionally handles image. Neither emits native video, so the comparison is about parsing images and documents, not generation.

Speed & latency

DeepSeek-V4-Pro is faster in interactive use: ~70 tok/s with 0.5s TTFT versus ~50 tok/s with 0.8s TTFT (about 1.4× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.

Context: window vs usable recall

Nominal windows are 1.05M for GPT-5.5 and 1M for DeepSeek-V4-Pro. Crucially, the larger nominal window does not win on usable recall: GPT-5.5 advertises 1.05M but DeepSeek-V4-Pro scores higher on effective-context (94 vs 90), i.e. it actually retains more of what it was given.

Price & total cost

DeepSeek-V4-Pro is the cheaper API at $0.44/$1.32 versus GPT-5.5 at $5/$30 per 1M input/output tokens — list input is about 11.4× lower. Cache discounts (GPT-5.5 50%) shift the effective bill, worked out below.

Chinese vs English

English: GPT-5.5 94 vs DeepSeek-V4-Pro 82. Chinese: 76 vs 85. For Chinese-language production, DeepSeek-V4-Pro is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: GPT-5.5 95 vs DeepSeek-V4-Pro 82, so GPT-5.5 has the edge on structured tool use. Fine-tuning is available from GPT-5.5 and DeepSeek-V4-Pro. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

Cost worked example — same workload, real token math

Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.

Scenario · per monthGPT-5.5DeepSeek-V4-ProGap
List priceno cache applied$1,400100M in × $5  +  30M out × $30$84100M in × $0.44  +  30M out × $1.3216.67×gap
With caching90% of inputs cache-hit$1,17590M cached in × $2.5  +  10M in × $5  +  30M out × $30$84no published cache discount13.99×gap

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose DeepSeek-V4-Pro (coding 79 vs 75).
IF you serve real-time users and latency is a product KPI  →  choose DeepSeek-V4-Pro (~70 tok/s, 0.5s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose DeepSeek-V4-Pro ($$0.44/$$1.32 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose DeepSeek-V4-Pro (effective context 94 vs 90).
07

Frequently asked questions

Is GPT-5.5 worth the higher price over DeepSeek-V4-Pro?
At list the input rate is 11.4x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when GPT-5.5's stronger dimensions protect revenue; for routine volume DeepSeek-V4-Pro is the economical pick.
Does GPT-5.5's higher refusal rate matter in production?
GPT-5.5 refuses about 15% of prompts versus 5% for DeepSeek-V4-Pro. In unattended pipelines that means more retries, fallbacks and manual review, raising effective cost and latency even when the token price is lower.
How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, GPT-5.5 is about $1,175/month and DeepSeek-V4-Pro about $84/month after cache discounts ($1,400 and $84 at list).
Does the bigger context window actually matter?
Nominal windows are GPT-5.5 (1.05M) and DeepSeek-V4-Pro (1M), but usable recall follows the effective-context score (90 vs 94). Prefer the higher effective-context model for long-document work where nothing can be missed.
How do they differ for Chinese-language and data-residency use?
DeepSeek-V4-Pro is the Chinese model (Chinese score 85, domestic cloud, possible private deployment) while GPT-5.5 is the global model (Chinese 76, overseas API). Pick by language quality, access path and where data must reside.
Can I self-host either model?
DeepSeek-V4-Pro ships open weights and can be self-hosted (GPU permitting) for data control; GPT-5.5 is a closed managed API with no self-hosting. Choose open weights when residency or cost-at-scale dominates, managed API for convenience.