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

ERNIE 5.1 vs MiniMax M2.7

ERNIE 5.1 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.

VendorBaidu / MiniMax
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose ERNIE 5.1 when coding depth matter most; choose MiniMax M2.7 when lower cost, lower latency is the priority.

Choose ERNIE 5.1 if you…

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

Choose MiniMax M2.7 if you…

  • Light and fast
  • Open source
  • Low price
  • Best for: Light tasks, Open source, Low cost
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.

ERNIE 5.1 Higher overall
Baidu · #17 overall
Overall66
Coding62
Multimodal74
VS
MiniMax M2.7
MiniMax · #19 overall
Overall64
Coding59
Multimodal62

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.

DimensionERNIE 5.1MiniMax M2.7Verdict
VendorBaidu (CN)MiniMax (CN)Different vendors
Released2026.052026.05MiniMax M2.7 is newer
Overall (rank)66 · #1764 · #19ERNIE 5.1 +2
Coding62 · #1859 · #21ERNIE 5.1 +3
Multimodal74 · #1662 · #22ERNIE 5.1 +12
Context window128K205KMiniMax M2.7 larger
Max output32K32KTie
Effective-context8285MiniMax M2.7 more reliable
Input $/1M$1.1$0.27MiniMax M2.7 cheaper
Output $/1M$3.3$1.08MiniMax M2.7 cheaper
Cache discountnonenoneTie
Speed~45 tok/s~70 tok/sMiniMax M2.7 faster
TTFT0.7s0.4sMiniMax M2.7 snappier
Function calling7872ERNIE 5.1 ahead
Refusal rate~12%~6%MiniMax M2.7 less restrictive
English6565Tie
Chinese9282ERNIE 5.1
Modalitiestext, imagetextdifferent coverage
Open weightsNoYesMiniMax M2.7 is open
Fine-tuningYesYes
Free tierERNIE Bot free; quota on the Qianfan platformHailuo AI free
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

ERNIE 5.1 leads the overall aggregate by 2 points (66 vs 64). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while MiniMax M2.7 remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a modest gap: ERNIE 5.1 scores 62 against 59. On multi-file edits, SWE-style tickets and long-horizon agent loops ERNIE 5.1 needs fewer correction turns; MiniMax M2.7 is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

ERNIE 5.1 leads multimodal 74 vs 62. 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

MiniMax M2.7 is faster in interactive use: ~70 tok/s with 0.4s 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 128K for ERNIE 5.1 and 205K for MiniMax M2.7. Effective-context scores point the same way as window size — MiniMax M2.7 is ahead on usable recall (85 vs 82), so prefer it for long-document work where details cannot be missed.

Price & total cost

MiniMax M2.7 is the cheaper API at $0.27/$1.08 versus ERNIE 5.1 at $1.1/$3.3 per 1M input/output tokens — list input is about 4.1× lower.

Chinese vs English

English: ERNIE 5.1 65 vs MiniMax M2.7 65. Chinese: 92 vs 82. 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: ERNIE 5.1 78 vs MiniMax M2.7 72, so ERNIE 5.1 has the edge on structured tool use. Fine-tuning is available from ERNIE 5.1 and MiniMax M2.7. 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 monthERNIE 5.1MiniMax M2.7Gap
List priceno cache applied$209100M in × $1.1  +  30M out × $3.3$59100M in × $0.27  +  30M out × $1.083.54×gap
With caching90% of inputs cache-hit$209no published cache discount$59no published cache discount3.54×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 ERNIE 5.1 (coding 62 vs 59).
IF you serve real-time users and latency is a product KPI  →  choose MiniMax M2.7 (~70 tok/s, 0.4s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose MiniMax M2.7 ($$0.27/$$1.08 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose MiniMax M2.7 (effective context 85 vs 82).
07

Frequently asked questions

Is ERNIE 5.1 worth the higher price over MiniMax M2.7?
At list the input rate is 4.1x 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 MiniMax M2.7 is the economical pick.
Does ERNIE 5.1's higher refusal rate matter in production?
ERNIE 5.1 refuses about 12% of prompts versus 6% for MiniMax M2.7. 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, ERNIE 5.1 is about $209/month and MiniMax M2.7 about $59/month after cache discounts ($209 and $59 at list).
Does the bigger context window actually matter?
Nominal windows are ERNIE 5.1 (128K) and MiniMax M2.7 (205K), but usable recall follows the effective-context score (82 vs 85). Prefer the higher effective-context model for long-document work where nothing can be missed.
Can I self-host either model?
MiniMax M2.7 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.
Which handles multimodal inputs better?
Multimodal scores are 74 (ERNIE 5.1) vs 62 (MiniMax M2.7), with modality coverage text/image versus text. Match the model to the input types your product actually receives.