Comparisons of Medium Open Source AI Models (40B-150B)

Open source AI models with between 40B to 150B parameters.

Models are considered open source (also commonly referred to as open weights) where their weights are accessible to download. This allows self-hosting on your own infrastructure and enables customizing the model such as through fine-tuning.

For more details including relating to our methodology, see our FAQs.

Alibaba logoQwen3.5 122B A10B and Mistral logoMistral Medium 3.5 are the highest intelligence Medium open source models, defined as those with 40B-150B parameters, followed by Alibaba logoQwen3.5 122B A10B & NVIDIA logoNVIDIA Nemotron 3 Super.

Highlights

Artificial Analysis Openness Index · Higher is better
Updated
Artificial Analysis Intelligence Index · Higher is better
Trainable parameters in billions

Openness

Artificial Analysis Openness Index: Score

Openness Index assesses model openness on a 0 to 100 normalized scale (higher is more open)
Reasoning models are indicated by a lightbulb icon

Intelligence

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR
Estimate (independent evaluation forthcoming)
Reasoning models are indicated by a lightbulb icon

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

Agentic real-world work tasks, (Elo-500)/2000

Agentic tool use

Agentic coding & terminal use

Coding

Reasoning & knowledge

Scientific reasoning

Physics reasoning

Long context reasoning

Agentic knowledge work, Elo

Agentic SaaS workflows

Legal agentic work, task all-pass rate

Agentic business operations

Instruction following

Long-horizon agentic tasks

Kubernetes incident root-cause analysis

Visual reasoning

Reasoning models are indicated by a lightbulb icon.

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Size

Model Size: Total and Active Parameters

Comparison between total model parameters and parameters active during inference
Reasoning models are indicated by a lightbulb icon

The total number of trainable weights and biases in the model, expressed in billions. These parameters are learned during training and determine the model's ability to process and generate responses.

The number of parameters actually executed during each inference forward pass, expressed in billions. For Mixture of Experts (MoE) models, a routing mechanism selects a subset of experts per token, resulting in fewer active than total parameters. Dense models use all parameters, so active equals total.

Intelligence vs. Active Parameters

Artificial Analysis Intelligence Index · Active parameters at inference time
Most attractive quadrant
Reasoning models are indicated by a lightbulb icon.

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

The number of parameters actually executed during each inference forward pass, expressed in billions. For Mixture of Experts (MoE) models, a routing mechanism selects a subset of experts per token, resulting in fewer active than total parameters. Dense models use all parameters, so active equals total.

Intelligence vs. Total Parameters

Artificial Analysis Intelligence Index · Size in parameters (billions)
Most attractive quadrant
Reasoning models are indicated by a lightbulb icon.

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

The total number of trainable weights and biases in the model, expressed in billions. These parameters are learned during training and determine the model's ability to process and generate responses.

Context Window

Context Window

Context window: tokens limit · Higher is better
Reasoning models are indicated by a lightbulb icon

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Further details

Weights
Provider Benchmarks
Qwen3.5 122B A10B (Reasoning)
Alibaba logoAlibaba
32
125B
10B active at inference time
262k
$0.7
135
SiliconFlowDeepInfraNovita
+2
Mistral Medium 3.5
Mistral logoMistral
30
128B
256k
$1.2
70
Mistral
Qwen3.5 122B A10B (Non-reasoning)
Alibaba logoAlibaba
28
125B
10B active at inference time
262k
$0.7
149
DeepInfraAlibaba Cloud
NVIDIA Nemotron 3 Super 120B A12B (Reasoning)
NVIDIA logoNVIDIA
25
120.6B
12.7B active at inference time
1M
$0.2
148
DeepInfraBasetenCoreWeaveNebius
gpt-oss-120b (high)
OpenAI logoOpenAI
24
117B
5.1B active at inference time
131k
$0.2
271
ClarifaiCompactifAIFireworks
+19
Qwen3 Coder Next
Alibaba logoAlibaba
21
79.7B
3B active at inference time
256k
$0.4
101
NovitaAmazon BedrockTogether AIParasail
Mistral Small 4 (Reasoning)
Mistral logoMistral
20
119B
6.5B active at inference time
256k
$0.2
174
Mistral
Devstral 2
Mistral logoMistral
19
125B
256k
-
56
Mistral
HyperNova 60B 2605
Multiverse Computing logoMultiverse Computing
18
58.7B
4.8B active at inference time
131k
$0.1
345
CompactifAI
K2 Think V2
MBZUAI Institute of Foundation Models logoMBZUAI Institute of Foundation Models
17
70B
262k
-
-
-
LongCat Flash Lite
LongCat logoLongCat
17
68.5B
3B active at inference time
256k
-
-
-
Qwen3 Next 80B A3B (Reasoning)
Alibaba logoAlibaba
17
80B
3B active at inference time
262k
$1.1
184
GMIAlibaba CloudGoogle
+2