Novita: Models Intelligence, Performance & Price
This analysis is intended to support you in choosing the best model provided by Novita for your use-case.
Most Intelligent
Updated
MiMo-V2.6-Pro
GLM-5.3 (max)GLM-5.3-Flash
DeepSeek V4.1 Flash (max)MiMo-V2.6-FlashIntelligence index
Total 81 models
Fastest
Nemotron 3 Nano (FP4)Nemotron 3 Nano (non-reasoning) (FP4)
Qwen3 Next 80B A3B
gpt-oss-20b (high)gpt-oss-120b (low)Output speed
Total 81 models
Lowest Price
Llama 3.1 8Bgpt-oss-20b (low)gpt-oss-20b (high)MiMo-V2.6-FlashGLM-4.7-FlashBlended price (per 1M tokens)
Total 81 models
Novita offers 81 models, each with different intelligence, performance, and pricing characteristics. Below is a comparison of the key metrics across models.
- For intelligence, the top models on Novita are MiMo-V2.6-Pro (46), GLM-5.3 (max) (45), and GLM-5.3-Flash (42).
- For output speed, the fastest models are Nemotron 3 Nano (FP4) (310 t/s), Nemotron 3 Nano (non-reasoning) (FP4) (309 t/s), and Qwen3 Next 80B A3B (182 t/s). Speed varies significantly across models, with a 77% difference between the fastest and slowest.
- For latency, Llama 3.1 8B (0.95s), Nemotron 3 Nano (non-reasoning) (FP4) (1.02s), and Llama 4 Maverick (FP8) (1.08s) offer the lowest time to first answer token.
- For pricing, Llama 3.1 8B ($0.02), gpt-oss-20b (low) ($0.05), and gpt-oss-20b (high) ($0.05) offer the lowest blended prices per 1M tokens. Prices vary up to 2.7x across models.
- For context window size, GLM-5.3-Flash (1M), DeepSeek V4 Pro 0813 (max) (1M), and GLM-5.2 (max) (FP8) (1M) support the largest context windows on Novita.
Highlights
Intelligence Evaluations
Artificial Analysis Intelligence Index
Intelligence Evaluations
Agentic knowledge work, (Elo-500)/2000
Agentic real-world work tasks, (Elo-500)/2000
Agentic SaaS workflows
Agentic coding & terminal use
Coding
Reasoning & knowledge
Professional document reasoning, All-pass
Physics reasoning
Knowledge
1 - hallucination rate
Long context reasoning
Legal agentic work, criterion pass rate
Agentic business operations
Agentic scientific research workflows in a terminal
Quantitative analysis on spreadsheets & documents
Kubernetes incident root-cause analysis
Visual reasoning
Medical long context reasoning
Intelligence Index vs. Price
Context Window
Context Window
Pricing
Intelligence Index vs. Price
Performance Summary
Output Speed vs. Price
Speed
Measured by Output Speed (tokens per second)
Output Speed
Latency
Measured by Time (seconds) to First Token
Latency: Time To First Answer Token
End-to-End Response Time
Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed
End-to-End Response Time vs. Price
Further Analysis | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
MiMo-V2.6-Pro | 1M | Open | 46 | $0.13 | 43 | 3.93 | 62.57 | 46.91 | |||
GLM-5.3 (max) | 1M | Open | 45 | $2.00 | 75 | 1.95 | 35.24 | 26.63 | |||
GLM-5.3-Flash | 1.05M | Open | 42 | $0.29 | 61 | 2.60 | 43.51 | 32.72 | |||
DeepSeek V4.1 Flash (max) | 524k | Open | 39 | $0.24 | 133 | 2.16 | 20.92 | 15.01 | |||
MiMo-V2.6-Flash | 1M | Open | 38 | $0.06 | 57 | 4.37 | 48.38 | 35.20 | |||
DeepSeek V4 Pro 0813 (max) | 1.05M | Open | 36 | $0.70 | 77 | 2.22 | 34.84 | 26.10 | |||
DeepSeek V4 Flash 0731 (max) | 1.05M | Open | 34 | $0.26 | 122 | 1.61 | 22.04 | 16.34 | |||
GLM-5.2 (max) (FP8) | 1.05M | Open | 34 | $0.88 | 75 | 1.88 | 35.12 | 26.59 | |||
DeepSeek V4 Pro (max) | 1.05M | Open | 30 | $1.09 | 80 | 1.88 | 62.79 | 54.66 | |||
DeepSeek V4 Pro (high) | 1.05M | Open | 30* | -- | 81 | 1.90 | 32.83 | 24.72 | |||
 MiniMax-M3 | 1M | Open | 29 | $0.46 | 108 | 1.25 | 24.44 | 18.55 | |||
GLM-5 FP8 | 203k | Open | 28* | -- | 67 | 2.05 | 55.54 | 46.07 | |||
 Kimi K2.6 | 262k | Open | 27 | $0.67 | 63 | 2.41 | 80.50 | 70.21 | |||
GLM-5.1 (FP8) | 205k | Open | 26 | $1.07 | 48 | 3.50 | 92.54 | 78.66 | |||
MiMo-V2.5-Pro | 1.05M | Open | 26 | $0.07 | 30 | 2.32 | 85.83 | 66.81 | |||
Kimi K2.7 Code | 262k | Open | 26 | $0.55 | 76 | 3.56 | 39.30 | 29.19 | |||
 Hy3 | 262k | Open | 25 | $0.07 | 76 | 3.74 | 36.83 | 26.48 | |||
MiMo-V2.5 | 1.05M | Open | 25* | -- | 45 | 26.19 | 82.10 | 44.73 | |||
DeepSeek V4 Flash (high) | 1.05M | Open | 24 | $0.15 | 141 | 1.68 | 14.00 | 8.78 | |||
GLM-5.1 (non-reasoning) (FP8) | 205k | Open | 24* | -- | 56 | 4.02 | 12.94 | -- | |||
DeepSeek V4 Flash (max) | 1.05M | Open | 24 | $0.13 | 132 | 1.58 | 47.85 | 42.49 | |||
Kimi K2.6 (non-reasoning) | 262k | Open | 24* | -- | 53 | 2.24 | 11.63 | -- | |||
Kimi K2.5 | 262k | Open | 23* | -- | 52 | 2.53 | 69.05 | 56.92 | |||
Qwen3.5 27B | 262k | Open | 23* | -- | 54 | 5.82 | 52.10 | 37.03 | |||
MiniMax-M2.5 | 205k | Open | 23* | -- | 92 | 1.87 | 29.05 | 21.74 | |||
MiniMax-M2.7 (FP8) | 205k | Open | 23 | -- | 53 | 2.23 | 58.00 | 46.36 | |||
GLM-4.7 | 205k | Open | 22* | -- | 34 | 5.15 | 78.71 | 58.85 | |||
Kimi K2 Thinking | 262k | Open | 22* | -- | 51 | 1.74 | 50.72 | 39.18 | |||
GLM-5 (non-reasoning) (FP8) | 203k | Open | 22* | -- | 64 | 1.90 | 9.67 | -- | |||
Qwen3.5 397B A17B (non-reasoning) | 262k | Open | 21* | -- | 87 | 1.71 | 7.48 | -- | |||
Qwen3.6 27B | 262k | Open | 21 | $0.62 | 56 | 2.95 | 114.15 | 102.20 | |||
MiniMax-M2.1 | 205k | Open | 21* | -- | 89 | 2.12 | 30.14 | 22.41 | |||
Qwen3.6 27B (non-reasoning) | 262k | Open | 20* | -- | 58 | 2.91 | 11.49 | -- | |||
Kimi K2.5 (non-reasoning) | 262k | Open | 19* | -- | 52 | 1.80 | 11.50 | -- | |||
Qwen3.5 35B A3B | 262k | Open | 19* | -- | 89 | 1.75 | 29.77 | 22.42 | |||
MiniMax-M2 | 205k | Open | 19* | -- | 86 | 2.02 | 31.07 | 23.24 | |||
GLM-4.6 | 205k | Open | 19* | -- | 33 | 5.39 | 81.54 | 60.92 | |||
Qwen3.5 397B A17B | 262k | Open | 18 | $0.47 | 86 | 1.77 | 44.40 | 36.85 | |||
MiMo-V2.5-Pro (non-reasoning) | 1.05M | Open | 18* | -- | 30 | 2.15 | 18.79 | -- | |||
Qwen3.6 35B A3B | 205k | Open | 18 | $0.31 | 124 | 1.37 | 49.09 | 43.67 | |||
GLM-4.7 (non-reasoning) | 205k | Open | 17* | -- | 32 | 5.52 | 20.96 | -- | |||
 Gemma 4 26B A4B | 262k | Open | 17* | -- | 154 | 1.57 | 17.84 | 13.02 | |||
Qwen3 Max | 262k | Proprietary | 16* | -- | 62 | 3.18 | 11.25 | -- | |||
Qwen3.5 122B A10B | 262k | Open | 16 | $0.32 | 96 | 1.97 | 28.10 | 20.90 | |||
Kimi K2 0905 | 262k | Open | 15* | -- | 53 | 1.37 | 10.88 | -- | |||
Qwen3.6 35B A3B (non-reasoning) | 205k | Open | 15* | -- | 138 | 1.46 | 5.09 | -- | |||
GLM-4.6 (non-reasoning) | 205k | Open | 15* | -- | 33 | 5.01 | 20.17 | -- | |||
GLM-4.7-Flash | 200k | Open | 15* | -- | 62 | 3.19 | 43.39 | 32.16 | |||
DeepSeek V3.1 Terminus (FP8) | 131k | Open | 15 | -- | 38 | 3.76 | 69.93 | 52.93 | |||
Gemma 4 31B | 262k | Open | 15 | $0.10 | 17 | 4.29 | 139.43 | 104.92 | |||
DeepSeek V3.1 Terminus (non-reasoning) (FP8) | 131k | Open | 14* | -- | 39 | 3.25 | 16.08 | -- | |||
Gemma 4 31B (non-reasoning) | 262k | Open | 14* | -- | 17 | 2.91 | 32.15 | -- | |||
DeepSeek V3.1 (non-reasoning) | 164k | Open | 14* | -- | 39 | 3.12 | 15.99 | -- | |||
DeepSeek V3.1 | 131k | Open | 13* | -- | 39 | 3.45 | 67.48 | 51.23 | |||
Qwen3 VL 235B A22B | 131k | Open | 13* | -- | 50 | 2.62 | 52.35 | 39.78 | |||
Gemma 4 26B A4B (non-reasoning) | 262k | Open | 13* | -- | 83 | 1.48 | 7.51 | -- | |||
DeepSeek R1 0528 | 164k | Open | 13* | -- | 27 | 1.31 | 95.04 | 74.99 | |||
Kimi K2 | 131k | Open | 13* | -- | 53 | 1.54 | 11.05 | -- | |||
Qwen3 235B A22B 2507 | 131k | Open | 13 | $0.11 | 65 | 2.32 | 40.53 | 30.57 | |||
Qwen3 235B 2507 | 131k | Open | 12* | -- | 56 | 1.61 | 10.59 | -- | |||
Qwen3 Coder 480B | 262k | Open | 12* | -- | 54 | 1.97 | 11.24 | -- | |||
MiniMax M1 80k | 1M | Open | 12* | -- | 89 | 1.79 | 30.03 | 22.59 | |||
gpt-oss-120b (high) | 131k | Open | 12 | $0.04 | 172 | 1.27 | 15.78 | 11.61 | |||
DeepSeek R1 (Jan) Turbo | 64k | Open | 11 | $0.11 | 21 | 2.10 | 139.49 | 113.27 | |||
DeepSeek R1 (Jan) | 64k | Open | 11 | $0.46 | -- | -- | -- | -- | |||
GLM-4.6V | 131k | Open | 11* | -- | 80 | 3.17 | 34.42 | 25.00 | |||
GLM-4.7-Flash (non-reasoning) | 200k | Open | 11* | -- | 63 | 8.74 | 16.66 | -- | |||
gpt-oss-120b (low) | 131k | Open | 10* | -- | 185 | 1.10 | 14.63 | 10.82 | |||
Llama 4 Maverick (FP8) | 1.05M | Open | 10* | -- | 73 | 0.90 | 7.71 | -- | |||
gpt-oss-20b (low) | 131k | Open | 10* | -- | 112 | 1.25 | 23.61 | 17.88 | |||
Qwen3 VL 235B A22B | 131k | Open | 10* | -- | 50 | 2.01 | 11.93 | -- | |||
Qwen3 Next 80B A3B | 131k | Open | 10* | -- | 185 | 1.70 | 4.40 | -- | |||
Qwen3 Coder Next (FP8) | 262k | Open | 9 | $0.33 | 165 | 2.82 | 5.85 | -- | |||
gpt-oss-20b (high) | 131k | Open | 9 | $0.01 | 123 | 1.30 | 21.59 | 16.23 | |||
Nemotron 3 Nano (FP4) | 262k | Open | 9 | $0.02 | 313 | 0.98 | 8.98 | 6.40 | |||
DeepSeek V3 (Dec) | 64k | Open | 8 | $0.05 | 54 | 2.63 | 11.94 | -- | |||
GLM-4.6V (non-reasoning) | 131k | Open | 8* | -- | 73 | 3.54 | 10.40 | -- | |||
Qwen3 235B (non-reasoning) (FP8) | 41k | Open | 8* | -- | 25 | 2.90 | 23.11 | -- | |||
Llama 4 Scout | 131k | Open | 8* | -- | 26 | 1.10 | 20.65 | -- | |||
Qwen3 VL 30B A3B | 131k | Open | 8* | -- | 110 | 1.56 | 6.13 | -- | |||
Llama 3.3 70B | 131k | Open | 8* | -- | 43 | 1.90 | 13.50 | -- | |||
GLM-4.5V | 65.5k | Open | 8* | -- | 45 | 2.76 | 58.49 | 44.58 | |||
Llama 3.1 8B | 16.4k | Open | 7* | -- | 142 | 0.94 | 4.48 | -- | |||
Nemotron 3 Nano (non-reasoning) (FP4) | 262k | Open | 7* | -- | 271 | 1.10 | 2.95 | -- | |||
GLM-4.5V (non-reasoning) | 65.5k | Open | 7* | -- | 47 | 2.82 | 13.38 | -- | |||
Llama 3 70B | 8.19k | Open | 5* | -- | -- | -- | -- | -- | |||
Gemma 3 27B | 98.3k | Open | 5 | $0.24 | 31 | 1.70 | 17.60 | -- | |||
Llama 3 8B | 8.19k | Open | 5* | -- | -- | -- | -- | -- | |||
Key definitions
Frequently Asked Questions
Common questions about Novita
Novita offers 81 models that we track: MiMo-V2.6-Pro, GLM-5.3 (max), GLM-5.3-Flash, DeepSeek V4.1 Flash (max), MiMo-V2.6-Flash, DeepSeek V4 Pro 0813 (max), DeepSeek V4 Flash 0731 (max), GLM-5.2 (max) (FP8), DeepSeek V4 Pro (max), DeepSeek V4 Pro (high), MiniMax-M3, GLM-5 FP8, Kimi K2.6, GLM-5.1 (FP8), MiMo-V2.5-Pro, Kimi K2.7 Code, Hy3, MiMo-V2.5, DeepSeek V4 Flash (high), GLM-5.1 (non-reasoning) (FP8), DeepSeek V4 Flash (max), Kimi K2.6 (non-reasoning), Kimi K2.5, Qwen3.5 27B, MiniMax-M2.5, MiniMax-M2.7 (FP8), GLM-4.7, Kimi K2 Thinking, GLM-5 (non-reasoning) (FP8), Qwen3.5 397B A17B (non-reasoning), Qwen3.6 27B, MiniMax-M2.1, Qwen3.6 27B (non-reasoning), Kimi K2.5 (non-reasoning), Qwen3.5 35B A3B, MiniMax-M2, GLM-4.6, Qwen3.5 397B A17B, MiMo-V2.5-Pro (non-reasoning), Qwen3.6 35B A3B, GLM-4.7 (non-reasoning), Gemma 4 26B A4B, Qwen3 Max, Qwen3.5 122B A10B, Kimi K2 0905, Qwen3.6 35B A3B (non-reasoning), GLM-4.6 (non-reasoning), GLM-4.7-Flash, Gemma 4 31B, Gemma 4 31B (non-reasoning), Qwen3 VL 235B A22B, Gemma 4 26B A4B (non-reasoning), DeepSeek R1 0528, Kimi K2, Qwen3 235B A22B 2507, Qwen3 235B 2507, Qwen3 Coder 480B, MiniMax M1 80k, gpt-oss-120b (high), DeepSeek R1 (Jan) Turbo, GLM-4.6V, GLM-4.7-Flash (non-reasoning), gpt-oss-120b (low), Llama 4 Maverick (FP8), gpt-oss-20b (low), Qwen3 VL 235B A22B, Qwen3 Next 80B A3B, Qwen3 Coder Next (FP8), gpt-oss-20b (high), Nemotron 3 Nano (FP4), DeepSeek V3 (Dec), GLM-4.6V (non-reasoning), Qwen3 235B (non-reasoning) (FP8), Llama 4 Scout, Qwen3 VL 30B A3B, Llama 3.3 70B, GLM-4.5V, Llama 3.1 8B, Nemotron 3 Nano (non-reasoning) (FP4), GLM-4.5V (non-reasoning), and Gemma 3 27B.
The most intelligent model available on Novita is MiMo-V2.6-Pro with an Intelligence Index score of 46.
The fastest model on Novita by output speed is Nemotron 3 Nano (FP4) at 310.3 tokens per second.
The model with the lowest time to first answer token on Novita is Llama 3.1 8B at 0.95s. Lower latency means faster initial response time.
The most affordable model on Novita by blended price is Llama 3.1 8B at $0.02 per 1M tokens (7:2:1 cache hit/input/output ratio).
Prices on Novita vary up to 119x across models, from $0.02 per 1M tokens for Llama 3.1 8B to $2.74 per 1M tokens for Qwen3 Max.
Yes, Novita offers an OpenAI-compatible API, making it easy to switch from OpenAI or use existing OpenAI SDK integrations.
79 of 81 models on Novita support JSON mode for structured output.
73 of 81 models on Novita support function calling (tool use).
Yes, Novita offers 49 reasoning models: MiMo-V2.6-Pro, GLM-5.3 (max), GLM-5.3-Flash, DeepSeek V4.1 Flash (max), MiMo-V2.6-Flash, DeepSeek V4 Pro 0813 (max), DeepSeek V4 Flash 0731 (max), GLM-5.2 (max) (FP8), DeepSeek V4 Pro (max), DeepSeek V4 Pro (high), MiniMax-M3, GLM-5 FP8, Kimi K2.6, GLM-5.1 (FP8), MiMo-V2.5-Pro, Kimi K2.7 Code, Hy3, MiMo-V2.5, DeepSeek V4 Flash (high), DeepSeek V4 Flash (max), Kimi K2.5, Qwen3.5 27B, MiniMax-M2.5, MiniMax-M2.7 (FP8), GLM-4.7, Kimi K2 Thinking, Qwen3.6 27B, MiniMax-M2.1, Qwen3.5 35B A3B, MiniMax-M2, GLM-4.6, Qwen3.5 397B A17B, Qwen3.6 35B A3B, Gemma 4 26B A4B, Qwen3.5 122B A10B, GLM-4.7-Flash, Gemma 4 31B, Qwen3 VL 235B A22B, DeepSeek R1 0528, Qwen3 235B A22B 2507, MiniMax M1 80k, gpt-oss-120b (high), DeepSeek R1 (Jan) Turbo, GLM-4.6V, gpt-oss-120b (low), gpt-oss-20b (low), gpt-oss-20b (high), Nemotron 3 Nano (FP4), and GLM-4.5V. Reasoning models use extended thinking to work through complex problems before providing an answer.
Yes, 80 of 81 models on Novita are open weight models: MiMo-V2.6-Pro, GLM-5.3 (max), GLM-5.3-Flash, DeepSeek V4.1 Flash (max), MiMo-V2.6-Flash, DeepSeek V4 Pro 0813 (max), DeepSeek V4 Flash 0731 (max), GLM-5.2 (max) (FP8), DeepSeek V4 Pro (max), DeepSeek V4 Pro (high), MiniMax-M3, GLM-5 FP8, Kimi K2.6, GLM-5.1 (FP8), MiMo-V2.5-Pro, Kimi K2.7 Code, Hy3, MiMo-V2.5, DeepSeek V4 Flash (high), GLM-5.1 (non-reasoning) (FP8), DeepSeek V4 Flash (max), Kimi K2.6 (non-reasoning), Kimi K2.5, Qwen3.5 27B, MiniMax-M2.5, MiniMax-M2.7 (FP8), GLM-4.7, Kimi K2 Thinking, GLM-5 (non-reasoning) (FP8), Qwen3.5 397B A17B (non-reasoning), Qwen3.6 27B, MiniMax-M2.1, Qwen3.6 27B (non-reasoning), Kimi K2.5 (non-reasoning), Qwen3.5 35B A3B, MiniMax-M2, GLM-4.6, Qwen3.5 397B A17B, MiMo-V2.5-Pro (non-reasoning), Qwen3.6 35B A3B, GLM-4.7 (non-reasoning), Gemma 4 26B A4B, Qwen3.5 122B A10B, Kimi K2 0905, Qwen3.6 35B A3B (non-reasoning), GLM-4.6 (non-reasoning), GLM-4.7-Flash, Gemma 4 31B, Gemma 4 31B (non-reasoning), Qwen3 VL 235B A22B, Gemma 4 26B A4B (non-reasoning), DeepSeek R1 0528, Kimi K2, Qwen3 235B A22B 2507, Qwen3 235B 2507, Qwen3 Coder 480B, MiniMax M1 80k, gpt-oss-120b (high), DeepSeek R1 (Jan) Turbo, GLM-4.6V, GLM-4.7-Flash (non-reasoning), gpt-oss-120b (low), Llama 4 Maverick (FP8), gpt-oss-20b (low), Qwen3 VL 235B A22B, Qwen3 Next 80B A3B, Qwen3 Coder Next (FP8), gpt-oss-20b (high), Nemotron 3 Nano (FP4), DeepSeek V3 (Dec), GLM-4.6V (non-reasoning), Qwen3 235B (non-reasoning) (FP8), Llama 4 Scout, Qwen3 VL 30B A3B, Llama 3.3 70B, GLM-4.5V, Llama 3.1 8B, Nemotron 3 Nano (non-reasoning) (FP4), GLM-4.5V (non-reasoning), and Gemma 3 27B.
Yes, provider performance can vary over time due to infrastructure changes, load balancing, and updates. We continuously benchmark all providers and display historical performance trends in the "Over Time" charts.
When choosing a model on Novita, consider: intelligence (for quality-sensitive tasks), output speed (for throughput-intensive tasks), latency (for interactive applications requiring quick first responses), pricing (for cost-sensitive workloads), and features like context window size, JSON mode, or function calling support.