Gemini 4 Argon vs Aya Expanse 32B
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Gemini 4 Argon by Google against Aya Expanse 32B by Cohere across real-world coding, reasoning, token economics, and latency.
Changez et Comparez les Modèles
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Live comparison: no in-depth editorial review has been published for this pair yet.
Gemini 4 Argon
Roi multimodal avec sortie 1MGoogle de DeepMind phare de pointe raisonnement moteur intégrant 1-millions-token sortie limits, autonome cybersecurity defense, et en temps réel audio/vision ingestion.
$2.00 / 1M
$10.00 / 1M
1M tokens
81.9%
Aya Expanse 32B
Multilingue de 32Bélevé-capacité 32B multilingue modèle offrant supérieur performances à travers 23 mondial langues avec rich nuance et 128K contexte.
$0.25 / 1M
$0.50 / 1M
128K tokens
33.5%
Différences Clés en un Coup d’Œil
- Aya Expanse 32B is 13.3x cheaper for API usage (input + output tokens combined).
- Gemini 4 Argon has a larger context window (1M vs 128K tokens).
- Gemini 4 Argon is faster at 115 tok/s vs 85 tok/s.
- Gemini 4 Argon leads on SWE-bench coding (81.9% vs 33.5%).
| Caractéristique | Gemini 4 Argon | Aya Expanse 32B |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 97 | 44 |
Provider | Cohere | |
Input Price Cost per million input tokens | $2.00 / 1M | $0.25 / 1M |
Output Price Cost per million output tokens | $10.00 / 1M | $0.50 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.47 / 1M | $0.14 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 1000K | 8K |
Throughput Speed Tokens generated per second | 115 tok/s | 85 tok/s |
SWE-bench Verified Real-world software engineering | 81.9% | 33.5% |
GPQA Diamond Graduate-level reasoning | 81.5% | 50% |
Cached Input Price Prompt caching discount per 1M tokens | $0.10 / 1M | $0.06 / 1M |
Qui gagne où ?
At-a-glance decision frameworkScores de Benchmarks Vérifiés
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latence et Temps de Réponse
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulateur Interactif de Coût de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini 4 Argon · Strengths & Key Advantages
- Groundbreaking 1,000,000 token maximum sortie génération capacité via long Decode Continuation
- 1M-token entrée window avec 99.7% GraphWalks recall (84.2% dans le 256K-1M range)
- natif traitement de complet audio, vidéo streams, et visuel données (91.7% sur LVBench)
- Half le token prix de d'Anthropic Opus 5.5 et #1 sur Chatbot Arena (1525 Elo)
Considerations & Trade-offs
- massif token outputs peut incur élevé absolute coûts if unconstrained (~62K sortie tokens par index tâche)
- $2/$10 tarification est un introductory 50% discount; standard rates revert à $4/$20 once le promotion ends
Aya Expanse 32B · Strengths & Key Advantages
- Substantially supérieur raisonnement et factual précision dans non-English langues
- Generous 128K fenêtre de contexte pour long multilingue document traduction
- à poids ouverts sous permissive license pour mondial researchers et enterprises
Considerations & Trade-offs
- Slightly inférieur codage benchmarks que English-centric 32B peers
- nécessite substantiel GPU VRAM pour multitour local hébergement
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini 4 Argon | Aya Expanse 32B |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.45 | $0.18 |
Output Tokens / Task Tokens generated per task | 75K | 28K |
Reasoning Tokens / Task Thinking tokens burned per task | 36K | 0K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | Gemini 4 Argon | Aya Expanse 32B |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-4-argon | aya-expanse-32b |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2026-09 | 2024-10 |
| Knowledge Cutoff | June 2026 | August 2024 |
| Architecture | Pathways Multimodal Sparse Mixture-of-Experts | High-Capacity Multilingual Transformer |
| Parameters | Confidential | 32B |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($0.25/1M in) across full 128K window |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0.1/1M with configurable TTL | Cached input at $0.06/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Built-in Google Search Grounding + Managed Python Code Execution Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Vertex AI Supervised Adapter Tuning & Context Distillation | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 20 GB VRAM (4-bit Quantized) · 69 GB VRAM (Native BF16) |
| Safety & Frontier Classification | Google DeepMind Frontier Safety Framework Verified | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text, vision, audio, video | text |
| Output Modalities | text | text |
Gemini 4 Argon vs Aya Expanse 32B: Réponses Rapides (FAQ)
Which is more intelligent, Gemini 4 Argon or Aya Expanse 32B?
Gemini 4 Argon is more intelligent. It scores 97 compared with 44 on the composite Intelligence Index.
Which model is faster?
Gemini 4 Argon is faster, generating 115 tokens per second compared with 85 tokens per second.
Which model is cheaper to run?
Aya Expanse 32B is cheaper at $0.14 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Aya Expanse 32B has lower latency, with a time to first token of 0.44s compared with 0.85s.
Which model has a larger context window?
Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 128K tokens.
Verdict
Choose Gemini 4 Argon for whole-dépôt génération de code, complet-book synthèse, vidéo compréhension, et multi-hour audio traitement, or choose Aya Expanse 32B for mondial d'entreprise communications, international juridique traduction, et académique recherche.
Questions fréquentes
Which is cheaper: Gemini 4 Argon or Aya Expanse 32B?+
Gemini 4 Argon costs $2/1M input and $10/1M output tokens, while Aya Expanse 32B costs $0.25/1M input and $0.5/1M output tokens.
Which model has a larger context window: Gemini 4 Argon or Aya Expanse 32B?+
Gemini 4 Argon supports 1M tokens whereas Aya Expanse 32B supports 128K tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: Google & Cohere Official Documentation