Benchmark Almanac

Claw-SWE-Bench

DeepSeek V4.1 Flash 81.7% leads since September 2026
Not in model cards

General-purpose agent harnesses such as OpenClaw do multilingual SWE-bench-style coding tasks through an adapter that turns their output into scorable patches.

40 upvotes on Hugging Face papers and 112 GitHub stars.

Made by
TokenRhythm
Released
June 2026
Kind
Fixing real repositories
Level
Expert
Scored
Checked automatically
Answers
Agent task
Tasks
All public
Strongest model tested
GPT-5.5 #20 on the capability index
Last model added
September 2026
Scores refreshed
November 12th, 2026

In the authors’ words

The software engineering capabilities of general-purpose agent harnesses remain underexplored, and existing benchmarks offer limited support for comparing these harnesses under consistent conditions. To address this gap, we introduce Claw-SWE-Bench, a unified benchmark that enables researchers to systematically assess the capabilities and efficiency of general-purpose harnesses on software engineering tasks. The benchmark contains 350 real-world GitHub issue-resolution instances across eight programming languages and 43 repositories and provides a shared adapter protocol to align task inputs, outputs, and execution environments across harnesses. Experiments show that general-purpose harnesses can effectively resolve real-world software issues and that their success rates and resource consumption vary substantially even when the underlying model is held fixed. To lower evaluation costs and support faster debugging and iteration, we also provide Claw-SWE-Bench Lite, an 80-instance subset designed to preserve the key evaluation properties of the full benchmark. We hope this benchmark will help researchers better evaluate and understand the performance of general-purpose harnesses on software engineering tasks and guide the development of more capable and efficient harnesses. The data is available at https://github.com/opensquilla/claw-swe-bench and https://huggingface.co/datasets/TokenRhythm/Claw-SWE-Bench.

Abstract of Claw-SWE-Bench: A Benchmark for Evaluating OpenClaw-style Agent Harnesses on Coding Tasks (arXiv:2606.12344, CC0)
17
Entries on its own leaderboard, 16 models we track

DeepSeek V4.1 Flash leads with 81.7% among models released by September 2026

Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Every run is in the next chart. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.

The newest model with a score here came out in September 2026, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:

  1. 1 DeepSeek V4.1 Flash Full-350; mean of 3 runs 81.7%
  2. 2 GPT-5.5 Full-350; single run 78%
  3. 3 Claude Opus 4.7 Full-350; single run 77.1%
  4. 4 MiMo-V2.6 Flash Full-350; single run 74.6%
  5. 5 GLM-5.2 Full-350; single run 74.3%
  6. 6 GLM-5.1 Full-350; mean of 3 runs 73.1%
  7. 7 Qwen3.7-Max Full-350; single run 73.1%
  8. 8 DeepSeek-V4-Pro Full-350; single run 71.7%
  9. 9 DeepSeek-V4-Flash Full-350; single run 70.3%
  10. 10 MiniMax-M3 Full-350; single run 69.7%
  11. 11 Hunyuan Hy3 Full-350; single run 69.4%
  12. 12 Kimi K2.7 Code Full-350; single run 68.3%
  13. 13 LongCat-2.0 Full-350; single run 67.1%
  14. 14 Kimi K2.6 Full-350; single run 66.9%
  15. 15 Qwen 3.6 Flash Full-350; mean of 3 runs 62.8%
  16. 16 MiniMax-M2.7 Full-350; single run 61.4%
  17. 17 Seed2.0 Mini Full-350; single run 48.6%

Source: Official Claw-SWE-Bench leaderboard

#EntryScoreSettingDateSource
1 DeepSeek V4.1 Flash 81.7% Full-350; mean of 3 runs, Hermes Agent Sep 2026 Official leaderboard
2 GPT-5.5 78% Full-350; single run, OpenClaw Apr 2026 Official leaderboard
3 Claude Opus 4.7 77.1% Full-350; single run, OpenClaw Apr 2026 Official leaderboard
4 MiMo-V2.6 Flash 74.6% Full-350; single run, OpenClaw Sep 2026 Official leaderboard
5 GLM-5.2 74.3% Full-350; single run, OpenClaw Jun 2026 Official leaderboard
6 GLM-5.1 73.1% Full-350; mean of 3 runs, Hermes Agent Apr 2026 Official leaderboard
7 Qwen3.7-Max 73.1% Full-350; single run, OpenClaw May 2026 Official leaderboard
8 DeepSeek-V4-Pro 71.7% Full-350; single run, OpenClaw Apr 2026 Official leaderboard
9 DeepSeek-V4-Flash 70.3% Full-350; single run, OpenClaw Apr 2026 Official leaderboard
10 MiniMax-M3 69.7% Full-350; single run, OpenClaw Jun 2026 Official leaderboard
11 Hunyuan Hy3 69.4% Full-350; single run, OpenClaw Official leaderboard
12 Kimi K2.7 Code 68.3% Full-350; single run, OpenClaw Jun 2026 Official leaderboard
13 LongCat-2.0 67.1% Full-350; single run, OpenClaw Jul 2026 Official leaderboard
14 Kimi K2.6 66.9% Full-350; single run, OpenClaw Apr 2026 Official leaderboard
15 Qwen 3.6 Flash 62.8% Full-350; mean of 3 runs, Hermes Agent Apr 2026 Official leaderboard
16 MiniMax-M2.7 61.4% Full-350; single run, OpenClaw Mar 2026 Official leaderboard
17 Seed2.0 Mini 48.6% Full-350; single run, OpenClaw Feb 2026 Official leaderboard

Cost–Resolve Pareto

The line joins the runs that no other run beats on both measures. We redrew this chart from the numbers on the official leaderboard.

40% 60% 80% 100% $1$10$100$1,000$10K Total API cost for Full-350 ($), log scale, lower is better Total Pass@1 Seed2.0 Mini (Full-350; single run): Total Pass@1 48.6%, total api cost for full-350 $19.4 MiniMax-M2.7 (Full-350; single run): Total Pass@1 61.4%, total api cost for full-350 $197 GLM-5.1 (Full-350; single run): Total Pass@1 72%, total api cost for full-350 $291 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 73.1%, total api cost for full-350 $389 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 71.2%, total api cost for full-350 $338 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 69.7%, total api cost for full-350 $391 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 69.1%, total api cost for full-350 $513 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 68.7%, total api cost for full-350 $525 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 65.7%, total api cost for full-350 $190 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 62.9%, total api cost for full-350 $86 Claude Opus 4.7 (Full-350; single run): Total Pass@1 77.1%, total api cost for full-350 $1,082 Kimi K2.6 (Full-350; single run): Total Pass@1 66.9%, total api cost for full-350 $634 GPT-5.5 (Full-350; single run): Total Pass@1 78%, total api cost for full-350 $1,399 DeepSeek-V4-Pro (Full-350; single run): Total Pass@1 71.7%, total api cost for full-350 $81.3 Qwen 3.6 Flash (Full-350; single run): Total Pass@1 60.9%, total api cost for full-350 $77.5 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 62.8%, total api cost for full-350 $104 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 60.9%, total api cost for full-350 $87 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 58.3%, total api cost for full-350 $69 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 56.8%, total api cost for full-350 $91 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 52.5%, total api cost for full-350 $175 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 45.1%, total api cost for full-350 $49 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 38.5%, total api cost for full-350 $39 Qwen3.7-Max (Full-350; single run): Total Pass@1 73.1%, total api cost for full-350 $436 MiniMax-M3 (Full-350; single run): Total Pass@1 69.7%, total api cost for full-350 $272 Kimi K2.7 Code (Full-350; single run): Total Pass@1 68.3%, total api cost for full-350 $271 GLM-5.2 (Full-350; single run): Total Pass@1 74.3%, total api cost for full-350 $304 LongCat-2.0 (Full-350; single run): Total Pass@1 67.1%, total api cost for full-350 $478 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 79.8%, total api cost for full-350 $50 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 79.6%, total api cost for full-350 $78 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 76.5%, total api cost for full-350 $41 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 76.1%, total api cost for full-350 $99 MiMo-V2.6 Flash (Full-350; single run): Total Pass@1 74.6%, total api cost for full-350 $22.3 Hunyuan Hy3 (Full-350; single run): Total Pass@1 69.4%, total api cost for full-350 $141. Not in our model list DeepSeek-V4-Flash (Full-350; single run): Total Pass@1 70.3%, total api cost for full-350 $8.2 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 81.7%, total api cost for full-350 $36 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 74.9%, total api cost for full-350 $13 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 71.5%, total api cost for full-350 $12 DeepSeek V4.1 Flash (Full-350; mean of 3 runs)DeepSeek V4.1 Flash (Full-350; mean of 3 runs)DeepSeek V4.1 Flash (Full-350; mean of 3 runs)DeepSeek-V4-Flash (Full-350; single run) 40% 60% 80% 100% $1$10$100$1,000$10K Total API cost for Full-350 ($), log scale, lower is better Total Pass@1 Seed2.0 Mini (Full-350; single run): Total Pass@1 48.6%, total api cost for full-350 $19.4 MiniMax-M2.7 (Full-350; single run): Total Pass@1 61.4%, total api cost for full-350 $197 GLM-5.1 (Full-350; single run): Total Pass@1 72%, total api cost for full-350 $291 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 73.1%, total api cost for full-350 $389 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 71.2%, total api cost for full-350 $338 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 69.7%, total api cost for full-350 $391 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 69.1%, total api cost for full-350 $513 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 68.7%, total api cost for full-350 $525 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 65.7%, total api cost for full-350 $190 GLM-5.1 (Full-350; mean of 3 runs): Total Pass@1 62.9%, total api cost for full-350 $86 Claude Opus 4.7 (Full-350; single run): Total Pass@1 77.1%, total api cost for full-350 $1,082 Kimi K2.6 (Full-350; single run): Total Pass@1 66.9%, total api cost for full-350 $634 GPT-5.5 (Full-350; single run): Total Pass@1 78%, total api cost for full-350 $1,399 DeepSeek-V4-Pro (Full-350; single run): Total Pass@1 71.7%, total api cost for full-350 $81.3 Qwen 3.6 Flash (Full-350; single run): Total Pass@1 60.9%, total api cost for full-350 $77.5 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 62.8%, total api cost for full-350 $104 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 60.9%, total api cost for full-350 $87 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 58.3%, total api cost for full-350 $69 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 56.8%, total api cost for full-350 $91 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 52.5%, total api cost for full-350 $175 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 45.1%, total api cost for full-350 $49 Qwen 3.6 Flash (Full-350; mean of 3 runs): Total Pass@1 38.5%, total api cost for full-350 $39 Qwen3.7-Max (Full-350; single run): Total Pass@1 73.1%, total api cost for full-350 $436 MiniMax-M3 (Full-350; single run): Total Pass@1 69.7%, total api cost for full-350 $272 Kimi K2.7 Code (Full-350; single run): Total Pass@1 68.3%, total api cost for full-350 $271 GLM-5.2 (Full-350; single run): Total Pass@1 74.3%, total api cost for full-350 $304 LongCat-2.0 (Full-350; single run): Total Pass@1 67.1%, total api cost for full-350 $478 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 79.8%, total api cost for full-350 $50 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 79.6%, total api cost for full-350 $78 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 76.5%, total api cost for full-350 $41 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 76.1%, total api cost for full-350 $99 MiMo-V2.6 Flash (Full-350; single run): Total Pass@1 74.6%, total api cost for full-350 $22.3 Hunyuan Hy3 (Full-350; single run): Total Pass@1 69.4%, total api cost for full-350 $141. Not in our model list DeepSeek-V4-Flash (Full-350; single run): Total Pass@1 70.3%, total api cost for full-350 $8.2 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 81.7%, total api cost for full-350 $36 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 74.9%, total api cost for full-350 $13 DeepSeek V4.1 Flash (Full-350; mean of 3 runs): Total Pass@1 71.5%, total api cost for full-350 $12 DeepSeek V4.1 Flash (Full-350; mean of 3 runs)DeepSeek V4.1 Flash (Full-350; mean of 3 runs)DeepSeek V4.1 Flash (Full-350; mean of 3 runs)DeepSeek-V4-Flash (Full-350; single run)
ModelSettingTotal Pass@1Total API cost for Full-350
DeepSeek V4.1 Flash Full-350; mean of 3 runs, Hermes Agent 81.7% $36
DeepSeek V4.1 Flash Full-350; mean of 3 runs, OpenClaw 79.8% $50
DeepSeek V4.1 Flash Full-350; mean of 3 runs, nanobot 79.6% $78
GPT-5.5 Full-350; single run, OpenClaw 78% $1,399
Claude Opus 4.7 Full-350; single run, OpenClaw 77.1% $1,082
DeepSeek V4.1 Flash Full-350; mean of 3 runs, DeepSeek Harness 76.5% $41
DeepSeek V4.1 Flash Full-350; mean of 3 runs, ZeroClaw 76.1% $99
DeepSeek V4.1 Flash Full-350; mean of 3 runs, Meta-Harness 74.9% $13
MiMo-V2.6 Flash Full-350; single run, OpenClaw 74.6% $22.3
GLM-5.2 Full-350; single run, OpenClaw 74.3% $304.13
GLM-5.1 Full-350; mean of 3 runs, Hermes Agent 73.1% $389
Qwen3.7-Max Full-350; single run, OpenClaw 73.1% $436.4
GLM-5.1 Full-350; single run, OpenClaw 72% $290.6
DeepSeek-V4-Pro Full-350; single run, OpenClaw 71.7% $81.3
DeepSeek V4.1 Flash Full-350; mean of 3 runs, GenericAgent 71.5% $12
GLM-5.1 Full-350; mean of 3 runs, OpenClaw 71.2% $338
DeepSeek-V4-Flash Full-350; single run, OpenClaw 70.3% $8.2
MiniMax-M3 Full-350; single run, OpenClaw 69.7% $271.8
GLM-5.1 Full-350; mean of 3 runs, ZeroClaw 69.7% $391
Hunyuan Hy3 Full-350; single run, OpenClaw 69.4% $141.1
GLM-5.1 Full-350; mean of 3 runs, DeepSeek Harness 69.1% $513
GLM-5.1 Full-350; mean of 3 runs, nanobot 68.7% $525
Kimi K2.7 Code Full-350; single run, OpenClaw 68.3% $270.9
LongCat-2.0 Full-350; single run, OpenClaw 67.1% $478
Kimi K2.6 Full-350; single run, OpenClaw 66.9% $633.7
GLM-5.1 Full-350; mean of 3 runs, Meta-Harness 65.7% $190
GLM-5.1 Full-350; mean of 3 runs, GenericAgent 62.9% $86
Qwen 3.6 Flash Full-350; mean of 3 runs, Hermes Agent 62.8% $104
MiniMax-M2.7 Full-350; single run, OpenClaw 61.4% $196.7
Qwen 3.6 Flash Full-350; single run, OpenClaw 60.9% $77.5
Qwen 3.6 Flash Full-350; mean of 3 runs, OpenClaw 60.9% $87
Qwen 3.6 Flash Full-350; mean of 3 runs, ZeroClaw 58.3% $69
Qwen 3.6 Flash Full-350; mean of 3 runs, DeepSeek Harness 56.8% $91
Qwen 3.6 Flash Full-350; mean of 3 runs, nanobot 52.5% $175
Seed2.0 Mini Full-350; single run, OpenClaw 48.6% $19.4
Qwen 3.6 Flash Full-350; mean of 3 runs, Meta-Harness 45.1% $49
Qwen 3.6 Flash Full-350; mean of 3 runs, GenericAgent 38.5% $39

The best score, 81.7%, costs $0.10 a task

Runs on the cost frontier score higher than any run that's cheaper. The costs are the leaderboard's own estimates, so compare them only within this benchmark.

DeepSeek Cost frontier One model at each effort level
0% 20% 40% 60% 80% 100% $0.01 $0.10 $1.00 $10 Cost per task, log scale DeepSeek V4.1 Flash, Full-350; mean of 3 runs DeepSeek V4.1 Flash, Full-350; mean of 3 runs DeepSeek-V4-Flash, Full-350; single run 0% 20% 40% 60% 80% 100% $0.01 $0.10 $1.00 $10 Cost per task, log scale DeepSeek V4.1 Flash, Full-350; mean of 3 runs DeepSeek V4.1 Flash, Full-350; mean of 3 runs

Source: Official Claw-SWE-Bench leaderboard

ModelEffortHarnessScoreCost per taskOutput tokens
DeepSeek V4.1 Flash Full-350; mean of 3 runs Hermes Agent 81.7% $0.10 38,000
DeepSeek V4.1 Flash Full-350; mean of 3 runs OpenClaw 79.8% $0.14 72,571
DeepSeek V4.1 Flash Full-350; mean of 3 runs nanobot 79.6% $0.22 38,857
GPT-5.5 Full-350; single run OpenClaw 78% $4.00 44,857
Claude Opus 4.7 Full-350; single run OpenClaw 77.1% $3.09 17,714
DeepSeek V4.1 Flash Full-350; mean of 3 runs DeepSeek Harness 76.5% $0.12 36,857
DeepSeek V4.1 Flash Full-350; mean of 3 runs ZeroClaw 76.1% $0.28 177,714
DeepSeek V4.1 Flash Full-350; mean of 3 runs Meta-Harness 74.9% $0.04 20,571
MiMo-V2.6 Flash Full-350; single run OpenClaw 74.6% $0.06 104,000
GLM-5.2 Full-350; single run OpenClaw 74.3% $0.87
GLM-5.1 Full-350; mean of 3 runs Hermes Agent 73.1% $1.11 19,714
Qwen3.7-Max Full-350; single run OpenClaw 73.1% $1.25
GLM-5.1 Full-350; single run OpenClaw 72% $0.83 20,000
DeepSeek-V4-Pro Full-350; single run OpenClaw 71.7% $0.23 31,429
DeepSeek V4.1 Flash Full-350; mean of 3 runs GenericAgent 71.5% $0.03 19,429
GLM-5.1 Full-350; mean of 3 runs OpenClaw 71.2% $0.97 23,143
DeepSeek-V4-Flash Full-350; single run OpenClaw 70.3% $0.02 36,857
GLM-5.1 Full-350; mean of 3 runs ZeroClaw 69.7% $1.12 12,286
MiniMax-M3 Full-350; single run OpenClaw 69.7% $0.78
GLM-5.1 Full-350; mean of 3 runs DeepSeek Harness 69.1% $1.47 15,143
GLM-5.1 Full-350; mean of 3 runs nanobot 68.7% $1.50 22,286
Kimi K2.7 Code Full-350; single run OpenClaw 68.3% $0.77
LongCat-2.0 Full-350; single run OpenClaw 67.1% $1.37 62,000
Kimi K2.6 Full-350; single run OpenClaw 66.9% $1.81 34,571
GLM-5.1 Full-350; mean of 3 runs Meta-Harness 65.7% $0.54 16,286
GLM-5.1 Full-350; mean of 3 runs GenericAgent 62.9% $0.25 14,571
Qwen 3.6 Flash Full-350; mean of 3 runs Hermes Agent 62.8% $0.30 20,857
MiniMax-M2.7 Full-350; single run OpenClaw 61.4% $0.56 25,714
Qwen 3.6 Flash Full-350; single run OpenClaw 60.9% $0.22 25,143
Qwen 3.6 Flash Full-350; mean of 3 runs OpenClaw 60.9% $0.25 27,143
Qwen 3.6 Flash Full-350; mean of 3 runs ZeroClaw 58.3% $0.20 17,429
Qwen 3.6 Flash Full-350; mean of 3 runs DeepSeek Harness 56.8% $0.26 27,714
Qwen 3.6 Flash Full-350; mean of 3 runs nanobot 52.5% $0.50 28,286
Seed2.0 Mini Full-350; single run OpenClaw 48.6% $0.06 61,714
Qwen 3.6 Flash Full-350; mean of 3 runs Meta-Harness 45.1% $0.14 21,714
Qwen 3.6 Flash Full-350; mean of 3 runs GenericAgent 38.5% $0.11 21,429

2 models have held number one on the official leaderboard since its release in June 2026

Lab claims count from the day the card came out, independent runs from the model’s release.

OpenAI DeepSeek
Own leaderboard Not tested since Sep 2026

Source: Official Claw-SWE-Bench leaderboard

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

On the benchmark’s own leaderboard Best so far
0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) DeepSeek V4.1 Flash GPT-5.5 GLM-5.1 MiniMax-M2.7 Seed2.0 Mini 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) DeepSeek V4.1 Flash GLM-5.1

Source: Official Claw-SWE-Bench leaderboard

No lab model card reports it yet

We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.

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  • SWE-bench Multilingual In use 300 GitHub-issue tasks across nine programming languages in SWE-bench format. Patch graded by repository tests. Claude Fable 5.2 96.6%
  • DeepSWE In use 113 original long-horizon engineering tasks across 91 repos and five languages, written from scratch. Hand-written verifiers accept alternative solutions. GPT-6 Astra 74.1%
  • SciCode In use Scientist-curated research coding problems split into subproblems across natural sciences. Code checked against test cases. Seed2.1 Pro 59.8%
  • Codeforces rating In use Model solves recent Codeforces contest problems. An Elo-style rating is computed from simulated contest performance. DeepSeek V4.1 Flash 3,471