MiniMax-M2.5-highspeed vs GPT-6.1 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare MiniMax-M2.5-highspeed by MiniMax against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.
Switch & Compare Any Models
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Live comparison: no in-depth editorial review has been published for this pair yet.
MiniMax-M2.5-highspeed
Fast AgentAccelerated cloud API endpoint of M2.5 delivering low-latency inference for high-frequency interactive agents and real-time chat.
$0.15 / 1M
$0.60 / 1M
204K tokens
N/A
GPT-6.1 Sol
Near-Astra ValueDelivers results close to GPT-6 Astra at roughly one fifth of the price — the latest 2026 release.
$2.00 / 1M
$10.00 / 1M
1M tokens
82.3%
Key Differences at a Glance
- MiniMax-M2.5-highspeed is 15.4x cheaper for API usage (input + output tokens combined).
- GPT-6.1 Sol has a larger context window (1M vs 204K tokens).
- MiniMax-M2.5-highspeed is faster at 150 tok/s vs 120 tok/s.
| Feature | MiniMax-M2.5-highspeed | GPT-6.1 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 78 | 94 |
Provider | MiniMax | OpenAI |
Input Price Cost per million input tokens | $0.15 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $0.60 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.10 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 204K tokens~306 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 8K | 128K |
Throughput Speed Tokens generated per second | 150 tok/s | 120 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 82.3% |
GPQA Diamond Graduate-level reasoning | N/A | 80.8% |
Cached Input Price Prompt caching discount per 1M tokens | $0.01 / 1M | $0.10 / 1M |
Who Wins Where?
At-a-glance decision frameworkEvaluations ongoing
Empirical Head-to-Head Benchmark Scores
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.
Latency & Response Time
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Real-Time Interactive Token Cost Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
MiniMax-M2.5-highspeed · Strengths & Key Advantages
- Rapid 150 tokens/sec streaming throughput with sub-300ms initial response
- Affordable API price point ($0.15 / 1M input) paired with 204K context
- High concurrency tolerance for customer-facing applications
Considerations & Trade-offs
- Lower precision on deep architectural software refactoring than dense flagships
- Hosted endpoint without local offline execution options
GPT-6.1 Sol · Strengths & Key Advantages
- Near-Astra results at roughly a fifth of the cost
- Excellent coding and long-horizon agent performance
- Strong reliability with far lower latency than Astra
- Near-flagship results at roughly a fifth of the price
Considerations & Trade-offs
- Still marginally behind Astra on the very hardest reasoning
- Same price as GPT-6 Sol, so the upgrade decision is easy
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | MiniMax-M2.5-highspeed | GPT-6.1 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.04 | $2.05 |
Output Tokens / Task Tokens generated per task | 12K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 36K |
Technical Specifications
Architecture, release timeline, capabilities, and modalities.
| Feature | MiniMax-M2.5-highspeed | GPT-6.1 Sol |
|---|---|---|
| Official API Model ID (SDK) | minimax-m2-5-highspeed | gpt-6-1-sol |
| API Protocol | MiniMax REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-02 | 2026-09 |
| Knowledge Cutoff | December 2025 | April 2026 |
| Architecture | Latency-Optimized Hosted Cloud Transformer | Near-Astra unified reasoning model |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.15/1M in) across full 204K window | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.015/1M tokens | Automatic prefix caching at $0.1/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | MiniMax Production Safety & Alignment Verified | OpenAI Preparedness Framework Audited & System Card Published |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision |
| Output Modalities | text | text |
MiniMax-M2.5-highspeed vs GPT-6.1 Sol: Quick Answers
Which is more intelligent, MiniMax-M2.5-highspeed or GPT-6.1 Sol?
GPT-6.1 Sol is more intelligent. It scores 94 compared with 78 on the composite Intelligence Index.
Which model is faster?
MiniMax-M2.5-highspeed is faster, generating 150 tokens per second compared with 120 tokens per second.
Which model is cheaper to run?
MiniMax-M2.5-highspeed is cheaper at $0.10 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
MiniMax-M2.5-highspeed has lower latency, with a time to first token of 0.27s compared with 1.12s.
Which model has a larger context window?
GPT-6.1 Sol has a larger context window, supporting 1M tokens compared with 204K tokens.
Verdict
Choose MiniMax-M2.5-highspeed for customer support bots, real-time code completion, and interactive chat interfaces, or choose GPT-6.1 Sol for the best value frontier model for professional and agentic work.
Frequently asked questions
Which is cheaper: MiniMax-M2.5-highspeed or GPT-6.1 Sol?+
MiniMax-M2.5-highspeed costs $0.15/1M input and $0.6/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: MiniMax-M2.5-highspeed or GPT-6.1 Sol?+
MiniMax-M2.5-highspeed supports 204K tokens whereas GPT-6.1 Sol supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- Aion-3.0 vs Aion-Mini: Benchmarks, Pricing & Speed ComparisonCompare
- Aion-3.0 vs Gemini 3.6 Flash: Benchmarks, Pricing & Speed ComparisonCompare
- Aion-Mini vs Laguna XS 2.1: Benchmarks, Pricing & Speed ComparisonCompare
- Aya Expanse 32B vs Llama 3.2 90B Vision: Benchmarks, Pricing & Speed ComparisonCompare
- Aya Expanse 8B vs Command R+: Benchmarks, Pricing & Speed ComparisonCompare
- Aya Expanse 8B vs Qwen 2.5 7B Instruct: Benchmarks, Pricing & Speed ComparisonCompare
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: MiniMax & OpenAI Official Documentation