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

DeepSeek-V4-Pro vs ERNIE 5.1

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

VendorDeepSeek / Baidu
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose DeepSeek-V4-Pro when coding depth, long-context reliability, lower refusal matter most; choose ERNIE 5.1 when its stronger dimensions is the priority.

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

Choose ERNIE 5.1 if you…

  • Optimized for Chinese
  • Search augmentation
  • Baidu integration
  • Mature enterprise services
  • Best for: Chinese, Search-augmented, Enterprise services
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.

DeepSeek-V4-Pro Higher overall
DeepSeek · #8 overall
Overall77
Coding79
Multimodal77
VS
ERNIE 5.1
Baidu · #17 overall
Overall66
Coding62
Multimodal74

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.

DimensionDeepSeek-V4-ProERNIE 5.1Verdict
VendorDeepSeek (CN)Baidu (CN)Different vendors
Released2026.042026.05ERNIE 5.1 is newer
Overall (rank)77 · #866 · #17DeepSeek-V4-Pro +11
Coding79 · #562 · #18DeepSeek-V4-Pro +17
Multimodal77 · #1374 · #16DeepSeek-V4-Pro +3
Context window1M128KDeepSeek-V4-Pro larger
Max output128K32KERNIE 5.1 longer
Effective-context9482DeepSeek-V4-Pro more reliable
Input $/1M$0.44$1.1DeepSeek-V4-Pro cheaper
Output $/1M$1.32$3.3DeepSeek-V4-Pro cheaper
Cache discountnonenoneTie
Speed~70 tok/s~45 tok/sDeepSeek-V4-Pro faster
TTFT0.5s0.7sDeepSeek-V4-Pro snappier
Function calling8278DeepSeek-V4-Pro ahead
Refusal rate~5%~12%DeepSeek-V4-Pro less restrictive
English8265DeepSeek-V4-Pro
Chinese8592ERNIE 5.1
Modalitiestexttext, imagedifferent coverage
Open weightsYesNoDeepSeek-V4-Pro is open
Fine-tuningYesYes
Free tierDeepSeek App free; new API users receive creditsERNIE Bot free; quota on the Qianfan platform
SOC2 / no-trainno / yesno / yes
Private deploymentYesYesBoth support it

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

DeepSeek-V4-Pro leads the overall aggregate by 11 points (77 vs 66). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while ERNIE 5.1 remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a clear gap: DeepSeek-V4-Pro scores 79 against 62. On multi-file edits, SWE-style tickets and long-horizon agent loops DeepSeek-V4-Pro needs fewer correction turns; ERNIE 5.1 is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

DeepSeek-V4-Pro leads multimodal 77 vs 74. A concrete modality difference: ERNIE 5.1 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 ~45 tok/s with 0.7s TTFT (about 1.6× 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 1M for DeepSeek-V4-Pro and 128K for ERNIE 5.1. Effective-context scores point the same way as window size — DeepSeek-V4-Pro is ahead on usable recall (94 vs 82), so prefer it for long-document work where details cannot be missed.

Price & total cost

DeepSeek-V4-Pro is the cheaper API at $0.44/$1.32 versus ERNIE 5.1 at $1.1/$3.3 per 1M input/output tokens — list input is about 2.5× lower.

Chinese vs English

English: DeepSeek-V4-Pro 82 vs ERNIE 5.1 65. Chinese: 85 vs 92. For Chinese-language production, ERNIE 5.1 is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: DeepSeek-V4-Pro 82 vs ERNIE 5.1 78, so DeepSeek-V4-Pro has the edge on structured tool use. Fine-tuning is available from DeepSeek-V4-Pro and ERNIE 5.1. 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 monthDeepSeek-V4-ProERNIE 5.1Gap
List priceno cache applied$84100M in × $0.44  +  30M out × $1.32$209100M in × $1.1  +  30M out × $3.32.49×gap
With caching90% of inputs cache-hit$84no published cache discount$209no published cache discount2.49×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 62).
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 82).
07

Frequently asked questions

Is ERNIE 5.1 worth the higher price over DeepSeek-V4-Pro?
At list the input rate is 2.5x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when ERNIE 5.1's stronger dimensions protect revenue; for routine volume DeepSeek-V4-Pro is the economical pick.
Which is better for agentic coding?
DeepSeek-V4-Pro is decisively stronger for coding (79 vs 62 on the aggregate). The gap shows on SWE-style multi-file tasks and long agent loops that need fewer correction turns; ERNIE 5.1 is fine for routine scripts.
Does ERNIE 5.1's higher refusal rate matter in production?
ERNIE 5.1 refuses about 12% 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, DeepSeek-V4-Pro is about $84/month and ERNIE 5.1 about $209/month after cache discounts ($84 and $209 at list).
Does the bigger context window actually matter?
Nominal windows are DeepSeek-V4-Pro (1M) and ERNIE 5.1 (128K), but usable recall follows the effective-context score (94 vs 82). Prefer the higher effective-context model for long-document work where nothing can be missed.
Can I self-host either model?
DeepSeek-V4-Pro ships open weights and can be self-hosted (GPU permitting) for data control; ERNIE 5.1 is a closed managed API with no self-hosting. Choose open weights when residency or cost-at-scale dominates, managed API for convenience.