Qwen: Qwen3 235B A22B Instruct 2507
Server-rendered model summary page for indexing/share previews. Use the interactive explorer for full filtering and comparison.
Identifiers & provenance
- Primary ID
- qwen/qwen3-235b-a22b-2507
- OpenRouter ID
- qwen/qwen3-235b-a22b-2507
- Arena ID
- qwen3-235b-a22b-instruct-2507
- Canonical slug
- qwen/qwen3-235b-a22b-07-25
- Match method
- openrouter_name
- Match key
- qwen3-235b-a22b-instruct-2507
Source semantics
- Arena rank is a human-preference leaderboard signal, not a universal truth metric.
- OpenRouter usage/popularity reflects adoption/traffic, not benchmark quality.
- Pricing fields may differ by provider and can include extra modes beyond prompt/completion.
Read more on Methodology & data sources.
Description
Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following, logical reasoning, math, code, and tool usage. The model supports a native 262K context length and does not implement "thinking mode" (<think> blocks). Compared to its base variant, this version delivers significant gains in knowledge coverage, long-context reasoning, coding benchmarks, and alignment with open-ended tasks. It is particularly strong on multilingual understanding, math reasoning (e.g., AIME, HMMT), and alignment evaluations like Arena-Hard and WritingBench.
Raw fields snapshot
{
"id": "qwen/qwen3-235b-a22b-2507",
"name": "Qwen: Qwen3 235B A22B Instruct 2507",
"description": "Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following, logical reasoning, math, code, and tool usage. The model supports a native 262K context length and does not implement \"thinking mode\" (<think> blocks).\n\nCompared to its base variant, this version delivers significant gains in knowledge coverage, long-context reasoning, coding benchmarks, and alignment with open-ended tasks. It is particularly strong on multilingual understanding, math reasoning (e.g., AIME, HMMT), and alignment evaluations like Arena-Hard and WritingBench.",
"created": 1753119555,
"canonical_slug": "qwen/qwen3-235b-a22b-07-25",
"hugging_face_id": "Qwen/Qwen3-235B-A22B-Instruct-2507",
"source_type": "both",
"context_length": 262144,
"max_completion_tokens": null,
"is_moderated": false,
"architecture": {
"modality": "text->text",
"input_modalities": [
"text"
],
"output_modalities": [
"text"
],
"tokenizer": "Qwen3",
"instruct_type": null
},
"input_modalities": [
"text"
],
"output_modalities": [
"text"
],
"modality": "text->text",
"tokenizer": "Qwen3",
"instruct_type": null,
"supported_parameters": [
"frequency_penalty",
"include_reasoning",
"logit_bias",
"logprobs",
"max_tokens",
"min_p",
"presence_penalty",
"reasoning",
"reasoning_effort",
"repetition_penalty",
"response_format",
"seed",
"stop",
"structured_outputs",
"temperature",
"tool_choice",
"tools",
"top_k",
"top_logprobs",
"top_p"
],
"default_parameters": {},
"per_request_limits": null,
"top_provider": {
"context_length": 262144,
"max_completion_tokens": null,
"is_moderated": false
},
"pricing": {
"prompt": "0.000000071",
"completion": "0.0000001"
},
"PPM": {
"prompt": 0.071,
"completion": 0.1
},
"openrouter_raw": {
"id": "qwen/qwen3-235b-a22b-2507",
"canonical_slug": "qwen/qwen3-235b-a22b-07-25",
"hugging_face_id": "Qwen/Qwen3-235B-A22B-Instruct-2507",
"name": "Qwen: Qwen3 235B A22B Instruct 2507",
"created": 1753119555,
"description": "Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following, logical reasoning, math, code, and tool usage. The model supports a native 262K context length and does not implement \"thinking mode\" (<think> blocks).\n\nCompared to its base variant, this version delivers significant gains in knowledge coverage, long-context reasoning, coding benchmarks, and alignment with open-ended tasks. It is particularly strong on multilingual understanding, math reasoning (e.g., AIME, HMMT), and alignment evaluations like Arena-Hard and WritingBench.",
"context_length": 262144,
"architecture": {
"modality": "text->text",
"input_modalities": [
"text"
],
"output_modalities": [
"text"
],
"tokenizer": "Qwen3",
"instruct_type": null
},
"pricing": {
"prompt": "0.000000071",
"completion": "0.0000001"
},
"top_provider": {
"context_length": 262144,
"max_completion_tokens": null,
"is_moderated": false
},
"per_request_limits": null,
"supported_parameters": [
"frequency_penalty",
"include_reasoning",
"logit_bias",
"logprobs",
"max_tokens",
"min_p",
"presence_penalty",
"reasoning",
"reasoning_effort",
"repetition_penalty",
"response_format",
"seed",
"stop",
"structured_outputs",
"temperature",
"tool_choice",
"tools",
"top_k",
"top_logprobs",
"top_p"
],
"default_parameters": {},
"expiration_date": null
},
"categories": {
"text-expert": {
"score": 1451,
"rank_ub": 34,
"votes": 3718,
"ci_95": "±10"
},
"text-industry-software-and-it-services": {
"score": 1461,
"rank_ub": 38,
"votes": 24542,
"ci_95": "±5"
},
"text-industry-writing-and-literature-and-language": {
"score": 1397,
"rank_ub": 54,
"votes": 15710,
"ci_95": "±5"
},
"text-overall": {
"score": 1422,
"rank_ub": 44,
"votes": 71551,
"ci_95": "±3"
},
"text-industry-life-and-physical-and-social-science": {
"score": 1445,
"rank_ub": 43,
"votes": 11213,
"ci_95": "±6"
},
"text-industry-mathematical": {
"score": 1440,
"rank_ub": 33,
"votes": 3531,
"ci_95": "±10"
},
"text-industry-entertainment-and-sports-and-media": {
"score": 1376,
"rank_ub": 66,
"votes": 12653,
"ci_95": "±6"
},
"text-industry-business-and-management-and-financial-operations": {
"score": 1431,
"rank_ub": 35,
"votes": 13078,
"ci_95": "±6"
},
"text-industry-medicine-and-healthcare": {
"score": 1460,
"rank_ub": 34,
"votes": 3931,
"ci_95": "±10"
},
"text-industry-legal-and-government": {
"score": 1430,
"rank_ub": 44,
"votes": 4624,
"ci_95": "±9"
},
"text-instruction-following": {
"score": 1415,
"rank_ub": 38,
"votes": 18808,
"ci_95": "±5"
},
"text-math": {
"score": 1426,
"rank_ub": 37,
"votes": 4364,
"ci_95": "±9"
},
"text-creative-writing": {
"score": 1383,
"rank_ub": 60,
"votes": 9598,
"ci_95": "±6"
},
"text-multi-turn": {
"score": 1438,
"rank_ub": 36,
"votes": 12468,
"ci_95": "±6"
},
"text-hard-prompts": {
"score": 1447,
"rank_ub": 37,
"votes": 35982,
"ci_95": "±4"
},
"text-coding": {
"score": 1471,
"rank_ub": 40,
"votes": 14337,
"ci_95": "±6"
},
"text-hard-prompts-english": {
"score": 1452,
"rank_ub": 43,
"votes": 17687,
"ci_95": "±5"
},
"text-longer-query": {
"score": 1436,
"rank_ub": 42,
"votes": 16224,
"ci_95": "±5"
},
"text-english": {
"score": 1432,
"rank_ub": 48,
"votes": 33224,
"ci_95": "±4"
},
"text-chinese": {
"score": 1471,
"rank_ub": 30,
"votes": 3717,
"ci_95": "±11"
},
"text-french": {
"score": 1461,
"rank_ub": 24,
"votes": 1175,
"ci_95": "±20"
},
"text-spanish": {
"score": 1424,
"rank_ub": 33,
"votes": 1725,
"ci_95": "±16"
},
"text-russian": {
"score": 1412,
"rank_ub": 46,
"votes": 5552,
"ci_95": "±8"
},
"text-german": {
"score": 1416,
"rank_ub": 33,
"votes": 1293,
"ci_95": "±18"
},
"text-japanese": {
"score": 1378,
"rank_ub": 30,
"votes": 1082,
"ci_95": "±19"
},
"text-korean": {
"score": 1378,
"rank_ub": 27,
"votes": 1250,
"ci_95": "±19"
},
"text-exclude-ties": {
"score": 1415,
"rank_ub": 43,
"votes": 50208,
"ci_95": "±4"
}
},
"arena_model_id": "qwen3-235b-a22b-instruct-2507",
"leaderboard_name": "qwen3-235b-a22b-instruct-2507",
"match_method": "openrouter_name",
"match_key": "qwen3-235b-a22b-instruct-2507",
"match_input": "Qwen: Qwen3 235B A22B Instruct 2507",
"arena_aliases": []
}