Head-to-Head Model Comparison

ERNIE Speed vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
Share
Related topics (4)
BaiduAnthropiclightweightflagship

Compare ERNIE Speed by Baidu against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Head-to-Head Comparison

Switch & Compare Any Models

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Profile
Profile
Multi-Model Arena Stack:
5-Model Matrix Workbench

Live comparison: no in-depth editorial review has been published for this pair yet.

Popular Matchups:
Baidu

ERNIE Speed

Fast Budget

Fast, free-tier accessible language model offering rapid response generation for bulk processing and entry-level automation.

Intelligence Index68 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Anthropic

Claude Opus 5.5

Frontier Intelligence Titan

Anthropic's most intelligent model for complex reasoning, research, and strategic analysis.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Key Differences at a Glance

  • ERNIE Speed is 1.0x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 128K tokens).
  • ERNIE Speed is faster at 175 tok/s vs 78 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureERNIE SpeedClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
6894
Provider
BaiduAnthropic
Input Price
Cost per million input tokens
$0.00 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$0.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.00 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
4K128K
Throughput Speed
Tokens generated per second
175 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
N/A84.6%
GPQA Diamond
Graduate-level reasoning
N/A82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.00 / 1M$0.40 / 1M

Who Wins Where?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
ERNIE Speed
1.0x cheaper monthly runtime
Speed
ERNIE Speed
+124% faster generation
Context
Claude Opus 5.5
1M tokens window

Empirical Head-to-Head Benchmark Scores

Official evaluation metrics verified by independent third-party research labs.

ERNIE SpeedClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

N/Avs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

N/Avs82.3%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

64%vs91.5%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1205ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs66.4%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs83.1%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

N/Avs95.4%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

175 tok/s vs78 tok/s

Latency & Response Time

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
ERNIE Speed0.23s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
ERNIE Speed3.09s
Claude Opus 5.57.81s

Real-Time Interactive Token Cost Simulator

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
ERNIE Speed Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
ERNIE Speed saves approximately $24.60 / month (100%) under this workload.1.0x Savings

ERNIE Speed · Strengths & Key Advantages

  • Free of charge on Baidu Qianfan API for registered developers
  • Sub-250ms initial token generation and fast 175 tokens/sec throughput
  • Adequate accuracy for standard text summarization and sentiment tagging
Considerations & Trade-offs
  • Limited analytical depth on complex technical or scientific problems
  • Max output token ceiling of 4096 tokens

Claude Opus 5.5 · Strengths & Key Advantages

  • Unmatched autonomous multi-step agentic coding and refactoring
  • Flawless multi-document reasoning over 1M token context with no long-prompt surcharge
  • Highest composite Intelligence Index score measured (94/100), leading SWE-bench Verified at 84.6%
  • Precise tool execution with robust error-recovery loops
Considerations & Trade-offs
  • Premium output pricing ($20.00/M) plus heavy reasoning-token usage (~68K output tokens per complex task) keeps long agentic runs expensive
  • Long thinking times at maximum effort can push a single hard agentic task toward ~$3.85+

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricERNIE SpeedClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.00$3.85
Output Tokens / Task
Tokens generated per task
8K68K
Reasoning Tokens / Task
Thinking tokens burned per task
0K42K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

FeatureERNIE SpeedClaude Opus 5.5
Official API Model ID (SDK)ernie-speedclaude-opus-5-5-20260901
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIAnthropic Messages API + AWS Bedrock + Vertex AI
Release Date2024-032026-09
Knowledge CutoffDecember 2023June 2026
ArchitectureDistilled High-Throughput TransformerExtended Autonomous Hybrid Reasoning Transformer
ParametersConfidential / 8B ScaleConfidential
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Free across full context window (only KV-cache VRAM scales)Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix KV-caching in vLLM / SGLang (0 cost)$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 GB VRAM (Native BF16)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationOpen-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 ControlSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision
Output Modalitiestexttext

ERNIE Speed vs Claude Opus 5.5: Quick Answers

Which is more intelligent, ERNIE Speed or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 68 on the composite Intelligence Index.

Which model is faster?

ERNIE Speed is faster, generating 175 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

ERNIE Speed is cheaper at $0.00 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

ERNIE Speed has lower latency, with a time to first token of 0.23s compared with 1.40s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 128K tokens.

Verdict

Choose ERNIE Speed for bulk text classification, simple conversational routing, and zero-cost prototyping, or choose Claude Opus 5.5 for large-scale software development agents, enterprise codebases, and mission-critical scientific synthesis.

Frequently asked questions

Which is cheaper: ERNIE Speed or Claude Opus 5.5?+

ERNIE Speed costs $0/1M input and $0/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: ERNIE Speed or Claude Opus 5.5?+

ERNIE Speed supports 128K tokens whereas Claude Opus 5.5 supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Sources: Baidu & Anthropic Official Documentation