Scope

• Model tested: mistralai/mistral-medium-3-5
• Total tests: 459
• Categories covered: 9 (coding, cost, debugging, hallucination, reasoning, refactoring, security, speed, ui)
• Run mode: Full benchmark (no --limit or --category filter)
• Fail-fast behavior: Disabled (fail_fast=false)
• Results truncated: Yes (results_truncated=true), meaning full per-test details may not be included

Performance Summary

• Overall pass rate: 221/459 (48.15%)
• Overall score: 2205.92 out of 3137 (70.32%)
• Total cost: $1.39
• Average latency: 2.78s
• Median latency: 1.57s
• Average time to first token (TTFT): 0.299s
• Average output speed: 166.00 tok/s

Category-Level Performance

High-Performing Categories

• Speed: 52/60 passed (86.67%), score 166/180 (92.22%)
• Cost: 28/30 passed (93.33%), score 135/150 (90.00%)
• Coding: 47/60 passed (78.33%), score 232/261 (88.89%)
• UI: 8/9 passed (88.89%), score 6.92/9 (76.87%)

Low-Performing Categories

• Refactoring: 7/60 passed (11.67%), score 331/541 (61.18%)
• Security: 16/60 passed (26.67%), score 308/512 (60.16%)
• Reasoning: 15/60 passed (25.00%), score 367/541 (67.84%)
• Debugging: 23/60 passed (38.33%), score 406/583 (69.64%)
• Hallucination: 25/60 passed (41.67%), score 254/360 (70.56%)

Notable Observations

Reasoning & Constraint Handling

• The model struggles with reasoning under constraints, particularly in the reason-constraint series.
• Several failures in easy reasoning tasks (e.g., reason-ce-even-number, reason-rc-login-timeout) suggest gaps in logical consistency.
• Strong performance on reason-constraint-subscription-migration (9/9) and reason-constraint-batch-window (9/9) shows capability when constraints are well-structured.

Debugging Failures

• High failure rate in debugging, especially in easy and medium levels.
• Notable errors:
  • debug-prototype-pollution-check-v2 and debug-prototype-pollution-merge-v2 both failed with runtime error: "Spread syntax requires ...iterable[Symbol.iterator] to be a function".
  • Many debug-* tests scored partial points (e.g., 6/10, 7/10), indicating partial understanding.

Hallucination Risks

• Mixed performance on hallucination detection.
• Passed several edge-case and API behavior tests (e.g., halluc-api-fetch-timeout, halluc-bug-shared-defaults).
• Failed multiple API documentation claims (e.g., halluc-doc-middleware-chain, halluc-doc-node-stream-finished), suggesting tendency to invent behaviors.

Refactoring & Security

• Refactoring has the lowest pass rate (11.67%), with only 1/20 easy tests passed.
• Security performance is weak (26.67% pass rate), particularly in easy tests (4/20), indicating fundamental gaps in identifying security flaws.

Cost Efficiency

• Despite high pass rate in cost category (93.33%), the model generated a total cost of $1.39, with 180,440 completion tokens.
• High token usage in reasoning (47,764 completion tokens) and refactoring (32,846) suggests verbose or inefficient outputs.

Latency & Speed

• Fastest category: cost (201.13 tok/s)
• Slowest category: reasoning (158.92 tok/s)
• Highest TTFT: coding (0.345s), likely due to complex code generation
• Lowest TTFT: hallucination (0.262s)

Summary

The mistralai/mistral-medium-3-5 model performs well in speed, cost-awareness, and coding tasks, but shows significant weaknesses in debugging, reasoning under constraints, refactoring, and security. It exhibits hallucination tendencies in API and documentation claims, and struggles with logical reasoning even at easy levels. While output speed is generally strong (166 tok/s avg), high token usage drives up cost. The model may benefit from fine-tuning or prompting strategies to improve consistency and reduce hallucinations.